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Multiscale Intelligence Test.mhtml
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**Summary**:
The paper delves into the idea of testing an AI's common-sense reasoning abilities using linguistic disambiguation, especially through the Winograd Schema Challenge established in 2012. The initial belief was that successfully disambiguating natural language sentences required a machine to exhibit common-sense reasoning equivalent to humans. By 2023, however, large language models (LLMs) easily passed this test, indicating its inadequacy in assessing AI's genuine common-sense abilities.
The authors argue that relying on disambiguation as a test for common sense stems from an outdated belief associated with early AI theories, which suggests that understanding language depends on a vast underlying database of propositional knowledge. Modern LLMs, on the other hand, integrate semantic knowledge with linguistic competency, indicating that some knowledge might not be strictly propositional. This reveals the flaw in viewing the Winograd Schema Challenge as a definitive test for common-sense reasoning. The success of LLMs in this challenge suggests that not all semantic knowledge is propositional or can be expressed linguistically. Therefore, linguistic tasks might not be the best measures of genuine intelligence or common-sense.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-3" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Analysis</strong>:</p><p>The paper by Browning & LeCun highlights a pivotal change in the understanding of common-sense reasoning in artificial intelligence systems. The Winograd Schema Challenge was initially established as a gold standard for assessing an AI's ability to make sense of ambiguous linguistic contexts, typically by offering a pair of sentences that vary slightly but require a nuanced understanding of the context to be interpreted correctly.</p><p>However, the authors assert that the ability of contemporary Large Language Models (LLMs) to successfully navigate the Winograd Schema Challenge is not a clear-cut indication of their possession of human-like common-sense reasoning. The performance of these models has instead revealed limitations and flaws in the foundational assumptions upon which the challenge was built.</p><p>A few key points emerge from their analysis:</p><ol><li><p><strong>Propositional Knowledge Assumption</strong>: Early AI research believed that understanding language was tantamount to accessing a vast database of factual statements (propositions). This perspective is rooted in symbolic AI, which assumes that every piece of knowledge can be codified into neat, discrete chunks. However, LLMs challenge this notion by blending semantic and linguistic knowledge, suggesting that not everything we consider "knowledge" fits the propositional mold.</p></li><li><p><strong>Non-Propositional Knowledge</strong>: Browning & LeCun suggest that LLMs can manage tasks requiring disambiguation, not necessarily because they possess genuine common-sense reasoning, but because they have been trained on vast amounts of linguistic data. This training allows them to recognize patterns that are not strictly based on propositional knowledge, which might include tacit or intuitive understanding that is difficult to articulate.</p></li><li><p><strong>Limitations of Linguistic Tests</strong>: The authors contend that gauging intelligence or common-sense reasoning purely based on linguistic tasks might be insufficient. If an AI system can complete a linguistic challenge without demonstrating deeper understanding, it's an indication that the test may not be capturing the essence of what it means to have "common sense."</p></li></ol><p><strong>Implications</strong>:</p><p>The implications of this analysis are profound for the AI community:</p><ul><li><strong>Rethinking Benchmarks</strong>: There's a need to design new benchmarks that genuinely assess AI's common-sense abilities beyond mere linguistic competence.</li><li><strong>Beyond Language</strong>: Understanding that language is just one facet of intelligence and that common-sense reasoning extends beyond linguistic capabilities.</li><li><strong>Interdisciplinary Collaboration</strong>: Insights from neuroscience, cognitive science, and even philosophy might be crucial in constructing more meaningful tests for AI systems.</li></ul><p>In conclusion, while the Winograd Schema Challenge remains an interesting tool for assessing linguistic disambiguation in AI, it may not be the definitive measure of genuine intelligence or common-sense reasoning as once believed. As AI continues to evolve, so must the metrics and challenges designed to evaluate it.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-4" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">**Section Snippets:**
**The Winograd Schema Challenge:**
Introduced by Levesque and team in 2011, the Winograd Schema Challenge aimed to evaluate AI's common-sense reasoning via linguistic disambiguation. Contrasting it with the Turing Test, which Levesque felt was an easily manipulated and unusual benchmark, the Challenge focused on more typical, less adversarial conversational paths.
**The Propositional Picture of Semantic Knowledge:**
Historically, Western philosophy perceived knowledge as the linkage of representations for clear and distinct comprehension. However, this view had limitations, as pointed out by Kant in the 18th century. Kant noted its inapplicability to more complex judgments, highlighting the need for a more nuanced understanding.
**Early AI and the Propositional Picture:**
Early AI endeavors, often termed “Symbolic AI,” relied heavily on this propositional view of semantic knowledge. This approach was evident in the Turing test and implied that language was a mere reflection of underlying thoughts, asserting that a machine could possess human-like thought processes if it could effectively communicate all propositions.
**A Forced Rethinking of the Propositional Picture:**
For early AI proponents, the Winograd Schema Challenge seemed ideal for testing common-sense. The challenge's foundation lay in the belief that understanding ambiguous sentences depended on background knowledge, which was assumed to be entirely propositional. This led to the perspective that language and thought were closely linked, with each linguistic sentence being a manifestation of a deeper proposition.
**LLMs and Common-Sense:**
This section delves into Large Language Models (LLMs) and their understanding of common-sense. LLMs base their success on extracting statistical patterns from human texts and conversations, enabling them to demonstrate competence in linguistic tasks. The success of LLMs, particularly in linguistic comprehension, arises from their ability to detect these patterns.
**Conclusion:**
The paper traverses the journey of the propositional perspective of thought and its influence on early AI research. The inherent belief was that disambiguating ambiguous sentences using common-sense would require tapping into the right proposition. The paper also alludes to the underlying assumption that the act of thinking was solely about identifying the correct proposition, implying that an AI proficient in disambiguation possesses similar knowledge as humans.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-5" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Comprehensive Overview</strong>:</p><p>The paper by Jacob Browning & Yann LeCun delves deep into the conceptualization of knowledge, understanding, and common-sense reasoning, especially in the context of AI's progression. Below is an overview based on the provided section snippets:</p><p><strong>The Winograd Schema Challenge:</strong>
The Challenge was introduced as a new benchmark to evaluate the ability of AI systems in understanding and applying common-sense reasoning within linguistic contexts. Unlike the Turing Test, which could be seen as more adversarial and manipulative, the Winograd Schema Challenge was aimed at evaluating AI capabilities in a more typical, non-confrontational conversational setting.</p><p><strong>The Propositional Picture of Semantic Knowledge:</strong>
The concept of propositional knowledge has deep roots in Western philosophy. This perspective views knowledge as the connection between representations for understanding. However, as pointed out by philosophers like Kant, this view has clear limitations, especially when applied to complex judgments or nuanced understandings.</p><p><strong>Early AI and the Propositional Picture:</strong>
In the initial stages of AI development, often referred to as the era of "Symbolic AI," there was a significant emphasis on this propositional understanding of knowledge. The Turing test, for instance, was built on this foundational belief that language was merely an external manifestation of underlying propositional thoughts. This led to the notion that if a machine could emulate human-like linguistic capabilities, it was essentially emulating human-like thought processes.</p><p><strong>A Forced Rethinking of the Propositional Picture:</strong>
The Winograd Schema Challenge, in many ways, was an extension of this propositional understanding. The challenge's basis was the assumption that understanding and interpreting ambiguous sentences required accessing background knowledge. This background knowledge was believed to be propositional in nature. Hence, the underlying assumption was a tight interlinking of language and thought, where every linguistic expression was essentially a reflection of a deeper, underlying proposition.</p><p><strong>LLMs and Common-Sense:</strong>
With the advent of Large Language Models (LLMs), there was a paradigm shift. These models do not rely on explicit propositional knowledge databases. Instead, they are trained on vast datasets containing human-generated text, allowing them to identify and exploit statistical patterns. The proficiency of LLMs in linguistic tasks, including those in the Winograd Schema Challenge, is attributed to this ability to recognize and make use of these patterns.</p><p><strong>Conclusion:</strong>
The paper underscores the historical and philosophical trajectory of understanding knowledge, especially from a propositional lens, and how it has shaped early AI research. The paper suggests that the foundational belief was an intertwining of language and thought, where disambiguating any ambiguous sentence using common-sense meant accessing the relevant proposition. Furthermore, it hints at the challenge of equating linguistic proficiency, as seen in advanced LLMs, with genuine human-like knowledge and reasoning. The exploration raises questions about the adequacy of current benchmarks and the nature of intelligence and understanding in AI systems.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-6" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">**The Winograd Schema Challenge:**
In 2011, Levesque and his team unveiled the Winograd Schema Challenge as an alternative to the Turing Test. The Turing Test, in its design, could easily be exploited and didn't necessarily provide an accurate measure of genuine intelligence. It often led to machines providing deceptive, playful, or pre-set responses rather than showcasing actual comprehension. Instead, the Winograd Schema Challenge was designed to be a simpler, yet more rigorous assessment of machine intelligence.
Named after Terry Winograd's 1972 work on "Understanding Natural Language," the challenge highlighted the need for both syntactical and semantic evaluations when processing language. Winograd emphasized that certain ambiguous sentences cannot be clarified solely based on syntax. For instance, in the sentence, "The town councilors refused to give the angry demonstrators a permit because they feared violence," the pronoun "they" could refer to either the councilors or the demonstrators. However, human understanding, aided by background knowledge, interprets this as the councilors fearing potential violence from the demonstrators. This form of reasoning, which involves implicit background knowledge, is what Levesque and Winograd considered akin to human-like thinking.
The Winograd Schema Challenge originally comprised over a hundred such ambiguous sentences. The main objective was to test machines on sentences where a slight word change could shift the entire meaning. For instance, the word "it" in the sentences about a trophy being too large or small to fit inside a suitcase changes its reference based on the context. Such tasks, which humans effortlessly decode, were seen as measures of common-sense reasoning. The underlying assumption was that a machine capable of solving these ambiguities should possess an inherent understanding of the world.
However, the Challenge evolved with time. One significant version, WinoGrande, expanded the dataset to over 40,000 ambiguous sentences. The expansion aimed to deter Large Language Models (LLMs) from simply "memorizing" the answers. By 2021, LLMs had shown impressive results, achieving over 90% success, close to the 94% by humans. These models also demonstrated advanced linguistic abilities.
Yet, these achievements have been met with skepticism. Despite their successes, LLMs often generate nonsensical outputs or make egregious mistakes, prompting questions about their so-called "common-sense" understanding. Critics argue that acing the Winograd Schema Challenge doesn't necessarily equate to having common-sense. For a true measure, a more comprehensive test might be needed, possibly involving extensive reading and comprehension or following a sequence of instructions.
The crux of the debate now centers around understanding why resolving linguistic ambiguities might not be the golden standard for evaluating common-sense. Before devising new tests, it's essential to introspect why certain benchmarks, which initially seemed promising, ended up revealing very little about genuine machine intelligence and common-sense.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-7" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Reflection on the Winograd Schema Challenge Overview</strong>:</p><p>Your detailed overview captures the essence of the Winograd Schema Challenge and the implications it holds for the future of AI research. The Challenge was indeed a significant leap from the Turing Test, focusing on linguistic ambiguities to gauge an AI's common-sense understanding. However, as Large Language Models (LLMs) like GPT-3 and its successors began to ace the Challenge, it became evident that pure linguistic performance might not be a sufficient indicator of genuine understanding or common-sense reasoning.</p><p>Here's a breakdown of the central themes and their implications:</p><ol><li><p><strong>The Turing Test's Limitations:</strong> Turing's benchmark was groundbreaking for its time. However, as machines became adept at mimicking human-like responses without genuinely understanding them, it became clear that another, more nuanced benchmark was needed.</p></li><li><p><strong>Winograd's Ambiguities</strong>: Winograd's focus on syntactical and semantic nuances of language emphasized that genuine understanding goes beyond mere pattern recognition. The challenge presented sentences that required contextual knowledge to disambiguate, a task humans effortlessly perform.</p></li><li><p><strong>LLMs and the Challenge</strong>: The vast datasets on which LLMs were trained enabled them to perform impressively on the Winograd Schema Challenge. However, it's essential to note that these models function based on recognizing patterns in vast amounts of data, which doesn't necessarily equate to genuine understanding or reasoning.</p></li><li><p><strong>Beyond Linguistic Performance</strong>: The criticism that LLMs, despite their linguistic capabilities, sometimes produce nonsensical or inaccurate outputs underscores the limitation of relying solely on linguistic benchmarks. Genuine intelligence, as many argue, requires a deeper understanding that might span beyond language.</p></li><li><p><strong>Future Directions</strong>: The acknowledgment that the Winograd Schema Challenge may not be the definitive test of machine common-sense signifies the evolving nature of AI benchmarks. It suggests the need for a more comprehensive evaluation system that assesses understanding, reasoning, and perhaps even the ability to interact with the environment.</p></li></ol><p>In essence, while the Winograd Schema Challenge has provided valuable insights into the capabilities of modern AI, it has also highlighted the limitations of current benchmarks. As AI continues to advance, the search for a definitive measure of machine intelligence and common-sense reasoning remains an ongoing endeavor.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-8" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">**The Propositional Picture of Semantic Knowledge:**
Historically, knowledge in Western philosophy was conceived as the accurate linkage of representations to gain a clear and distinct perception of things. Knowledge was about correct judgment. However, by the end of the 18th century, Kant realized that this model was insufficient. It worked well for direct categorical judgments like "the ball is red", but stumbled with more complex disjunctive or hypothetical judgments, such as "either the ball is red or blue, but not both" or "if this ball were made of bronze, it wouldn’t float". Kant's breakthrough insight was that knowledge isn’t merely about direct perception but also involves conceptualizing, believing, and judging in forms that are often non-perceptual.
Post-Kantian thinkers extended this perspective, suggesting that to account for diverse logical forms, knowledge must be propositionally structured. Philosophers like Bolzano and Boole strived to develop a formal logic devoid of sensory, imagistic content, focusing purely on propositions and their logical relationships. This aligned with the growing scientific emphasis on objective knowledge that transcends individual biases, cultural context, or linguistic barriers. The ultimate aim was to achieve a universally representable form of knowledge.
Frege took this a step further by introducing a purely formal predicate logic. He conceptualized thoughts (or semantic knowledge) as concepts housed within propositions, all in an ideal "language of thought". Frege viewed these propositions as timeless truths, existing even before being thought of or recognized by anyone. He emphasized that natural language, though imprecise, still attempts to capture these propositions. According to Frege, propositions are vital for thought and knowledge since they can be unequivocally interpreted, classified as true or false, and are always coherent when logical rules are correctly applied.
Frege believed that we unveil these eternal propositions via logical analysis and empirical study. Logical analysis illuminates the structural form of thought, while empirical exploration uncovers content. The grand vision was to unify all valid propositions from diverse fields like logic, math, and science into a comprehensive, ideal science. This perspective was championed by thinkers like Wittgenstein, who saw the entire natural sciences as a collection of true propositions. Logical positivists like Carnap imagined an idealized representation of all knowledge through formal symbolic logic, assuming that such propositions could capture reality's essence.
In essence, the early 20th century witnessed a significant philosophical shift towards the propositional depiction of knowledge. This model promoted a clear, unambiguous representation of knowledge using hypothetico-deductive systems. As computation sciences burgeoned mid-century, this propositional framework greatly influenced their evolution.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-9" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); 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Several key themes and implications emerge from this:</p><ol><li><p><strong>Historical Foundations</strong>: The exposition establishes the initial Western philosophical understanding of knowledge as a mere representation or linkage of accurate judgments.</p></li><li><p><strong>Kant's Insight</strong>: Kant's realization that knowledge extends beyond direct perception to include conceptualizing, believing, and judging in non-perceptual forms marks a pivotal shift. His acknowledgment of the complexities inherent in knowledge, especially in hypothetical or disjunctive judgments, underscores the depth and nuance of human understanding.</p></li><li><p><strong>Shift to Propositional Knowledge</strong>: The journey from Kant's observations to Bolzano's and Boole's formal logic devoid of sensory content paints a picture of the philosophical momentum towards a universal, propositionally structured knowledge. This shift was grounded in the aspiration for objective, universally representable knowledge.</p></li><li><p><strong>Frege's Propositions</strong>: Frege's contribution is seminal. By situating thoughts within propositions and envisioning an ideal "language of thought", he fundamentally changed the discourse on knowledge and language. His belief in propositions as timeless truths which natural language tries to capture introduces a profound depth to the understanding of language, thought, and their interrelation.</p></li><li><p><strong>Impact on Sciences and Logic</strong>: The later adoption of this propositional viewpoint by thinkers like Wittgenstein and logical positivists like Carnap signified its pervasive influence. The belief that all of natural sciences could be rendered as a collection of true propositions or that an idealized representation of knowledge could encapsulate the essence of reality marks the height of the propositional perspective's dominance.</p></li><li><p><strong>Influence on Computation</strong>: The final point, touching upon the influence of this philosophical perspective on the nascent field of computation, is crucial. The early computational models and Artificial Intelligence efforts, which were largely symbolic in nature, drew heavily from this propositional framework, indicating a direct bridge between philosophical discourses and technological advancements.</p></li></ol><p>Overall, the narrative captures the intricate evolution of the propositional view of semantic knowledge. It lays the groundwork for understanding how philosophical developments in the conception of knowledge have had long-standing ramifications, not just in philosophy, but also in the realms of logic, science, and even the early computational models. The depiction serves as a testament to the intertwined nature of philosophy, science, and technology.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-10" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">The passage discusses the history and challenges faced by early Artificial Intelligence (AI) researchers, with a specific focus on the "propositional picture" of semantic knowledge. Here's a brief summary:
1. **Symbolic AI and the Propositional Picture**: Early AI, also known as "Symbolic AI", viewed semantic knowledge through a lens where all thoughts are propositional and can be expressed via language. This view underpinned the Turing test, which suggested that a machine capable of language communication can also think as humans do.
2. **Logical Deductions**: Early AI prioritized logical deductions, sidelining approaches like cybernetics and neural networks which didn't fit the propositional paradigm. This perspective influenced how early AI researchers approached tasks like machine translation.
3. **Universal Language of Thought**: There was a belief that all natural languages are expressing the same underlying propositions. Finding a universal language of thought could lead to better translation methodologies.
4. **Ambiguity in Language**: Early AI systems grappled with the inherent ambiguity of natural language. An example highlighted is the sentence "the box was in the pen", which can be interpreted in multiple ways based on the context. Resolving this ambiguity required machines to have access to vast amounts of "common sense" knowledge.
5. **Knowledge-Based Approaches**: To address the ambiguity challenge, Terry Winograd developed an approach where the system's semantic knowledge would guide its parsing of language. However, this approach underscored the difficulty of rapidly accessing and applying relevant information.
6. **Knowledge Representation**: Early AI researchers recognized the need for efficient knowledge representation. Instead of strictly defined concepts, knowledge was organized around "scripts", patterns of human language usage relevant to specific situations. However, this made handling metaphors, analogies, and other nuances challenging.
7. **Efforts in the 1980s**: The 1980s saw efforts to combine general propositional logics with simpler, domain-specific logics. There was also an ambitious project named "Cyc", initiated by Doug Lenat, aiming to create a universal encyclopedia of all common-sense knowledge. The goal was to equip a machine with the vast knowledge humans possess to facilitate fluent conversations.
8. **Challenges**: Even if the Cyc project could be completed, a significant challenge remained: how to connect various pieces of information in diverse ways that humans can, including handling metaphors, analogies, and other nuanced linguistic elements.
9. **Conclusion**: The propositional view of semantic knowledge greatly influenced early AI's trajectory, especially in the realm of natural language understanding. This lens emphasized the importance of disambiguating language and having a vast, machine-readable database of concepts to derive logical inferences.
In essence, the passage sheds light on the foundational beliefs and challenges of early AI, emphasizing the role of the propositional view of semantic knowledge in shaping the field's endeavors.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-11" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Reflection on the Symbolic AI and the Propositional Picture Overview</strong>:</p><p>Your summary captures the essence of early AI research and its deep-rooted connection with the propositional view of semantic knowledge. Some reflections on your overview:</p><ol><li><p><strong>Foundation in Symbolic AI</strong>: By grounding early AI research in the notion that all thought is propositional and expressible through language, you set the stage for the challenges and milestones that followed. This foundation in "Symbolic AI" differentiates the early stages of AI from the subsequent developments influenced by other models of cognition and computation.</p></li><li><p><strong>Emphasis on Logic</strong>: The prioritization of logical deductions and sidelining of alternate approaches like neural networks underlines the dominance of logical reasoning and rule-based models in early AI. It also highlights the early AI community's confidence in the viability of a logic-based solution for understanding human cognition.</p></li><li><p><strong>Language Ambiguity</strong>: By emphasizing the challenges posed by the inherent ambiguity of natural language, the summary underscores one of the pivotal difficulties faced by early AI researchers. The example "the box was in the pen" succinctly captures this issue and showcases why a purely logical or propositional approach might falter.</p></li><li><p><strong>Winograd's Contribution</strong>: Terry Winograd's approach exemplifies the lengths to which researchers went to handle language ambiguity. However, it also raises questions about the feasibility of such an approach given the infinite variety and complexity of human language and experience.</p></li><li><p><strong>Knowledge Representation</strong>: The introduction of "scripts" as a way to organize knowledge emphasizes the early AI community's evolving understanding. While it aimed at a more flexible model than rigid propositions, it also brought to light other challenges such as handling metaphors.</p></li><li><p><strong>The Ambition of Cyc</strong>: The Cyc project embodies the optimism and ambition of early AI. It sought to encapsulate all common-sense knowledge, a colossal task that encapsulates the essence of the propositional view's aspirations. However, its mention also alludes to the vast gap between ambition and reality, especially when faced with the nuanced, varied nature of human knowledge.</p></li><li><p><strong>Concluding Thoughts</strong>: The conclusion serves as a poignant reminder of the legacy of early AI research. While many of its aspirations and methods have since been revised or replaced, its foundational beliefs and the challenges it faced laid the groundwork for subsequent AI advancements.</p></li></ol><p>Overall, your summary encapsulates the grand vision, challenges, and inherent limitations of early AI research rooted in the propositional view of semantic knowledge. The narrative offers insights into how foundational beliefs can shape, guide, and sometimes constrain a field's trajectory. It serves as a testament to the iterative nature of scientific and technological progress, where understanding past endeavors is crucial for future innovations.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-12" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">This passage delves deep into the philosophy and cognitive science of AI, specifically the Winograd Schema Challenge. Here's a summarized breakdown:
1. **Winograd Schema Challenge and Common Sense**:
- This Challenge was seen as a test of AI's common sense. If an AI can disambiguate ambiguous sentences, it has to draw on background or common sense knowledge.
- The assumption was that all knowledge, even common sense, is propositional. Meaning, understanding a sentence is the same as understanding its underlying proposition.
2. **Shift from Propositional to Statistical Methods**:
- By the mid-1980s, there was a shift towards statistical approaches like neural networks. These didn't separate logic from the underlying semantics.
- However, Levesque et al., when introducing the Challenge in 2012, were skeptical of statistical methods. They still felt that a knowledge-based approach was superior.
3. **Rethinking the Propositional Picture**:
- Neural networks, particularly large language models (LLMs), challenged the original assumptions. These models don't rely on distinct syntax or semantics but predict the next word based on previous words. They organize knowledge through this prediction.
- The success of LLMs indicates that not all knowledge is propositional or easily expressed in language. Knowledge could be visual, intuitive, or tied to theory of mind, etc.
- If semantic knowledge can be non-propositional, a machine could know a lot and yet lack common sense. It suggests that common sense isn't just about language understanding but involves other competencies.
4. **Implication for the Winograd Schema Challenge**:
- Without a strong propositional framework, the Challenge's relevance is questioned. Disambiguation might only tell us about language competence, not holistic common sense.
- If that's true, why prioritize disambiguation tasks over other tasks like driving or playing a game? These tasks also test knowledge and competencies, yet they might give a more rounded idea of common sense than mere linguistic tests.
- The conclusion is that common sense might not be best captured by linguistic or disambiguation tasks. Common sense might entail a range of skills and abilities, not just understanding language.
The text grapples with the complexities of defining and testing common sense in AI, raising questions about the methods and assumptions that guide AI development and evaluation.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-13" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text 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32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Reflection on the Winograd Schema Challenge and the Philosophy of AI Overview</strong>:</p><p>Your breakdown delves into the interplay between the Winograd Schema Challenge and the broader philosophical understanding of AI, providing insightful takeaways:</p><ol><li><p><strong>Winograd Schema Challenge's Propositional Assumptions</strong>:</p><ul><li>By framing the Challenge within the propositional knowledge paradigm, you've highlighted its roots and foundational assumptions. This sets the context for the rest of the passage and the philosophical shifts that would follow.</li></ul></li><li><p><strong>Statistical vs. Propositional Paradigms</strong>:</p><ul><li>The transition towards statistical models in the 1980s was a watershed moment in AI research. Your summary effectively contrasts this with the skepticism shown by Levesque and others, illustrating the tension between two primary AI research philosophies of the era.</li></ul></li><li><p><strong>Redefining the Nature of Knowledge with LLMs</strong>:</p><ul><li>This section captures the transformative impact of LLMs on AI understanding. By challenging the traditionally accepted definitions of knowledge, LLMs have led the field to reassess long-held beliefs about the nature of semantic knowledge.</li><li>The idea that knowledge can be non-propositional, suggesting that machines might have vast knowledge but still lack common sense, is a profound insight. It underscores the multifaceted nature of common sense and the limitations of a purely propositional approach.</li></ul></li><li><p><strong>Implications for AI Benchmarking</strong>:</p><ul><li>By questioning the singular emphasis on disambiguation tasks, your breakdown pushes the reader to ponder the very benchmarks used to gauge AI proficiency.</li><li>Your point about other competencies like driving or playing games offering a potentially richer perspective on common sense is particularly striking. It suggests that while linguistic proficiency is important, it's just one facet of the rich tapestry of skills and abilities that comprise common sense.</li></ul></li></ol><p>Your summary effectively highlights the fluidity of AI research paradigms and the evolving understanding of what constitutes knowledge and common sense. Through the lens of the Winograd Schema Challenge, you've portrayed the shifts in AI philosophy, hinting at the deeper complexities and challenges of accurately capturing and replicating human-like thinking and reasoning in machines. The text serves as a contemplative reflection on the measures and benchmarks we use to assess AI, prompting a reevaluation of what it truly means for a machine to "understand" and "think."</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-14" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">This section discusses the capabilities of Large Language Models (LLMs) and their potential understanding of common-sense. Here's a brief summary:
1. **LLMs and Common-sense Knowledge**: LLMs are designed to recognize patterns in text and derive statistical information based on how words and sentences are structured. The section questions whether this pattern recognition equates to genuine understanding or merely captures linguistic forms.
2. **Knowledge Leakage**: The text discusses the concept of "knowledge leakage" where the statistical patterns extracted from texts inadvertently capture semantic knowledge. However, the line between linguistic form and semantic content is debated.
3. **Success in Common-sense Tasks**: LLMs have shown proficiency in many common-sense tasks. The text suggests that this success arises from the models' ability to detect linguistic patterns and word usage typical of human language.
4. **Reasons for LLMs' Success**:
- LLMs often encounter stereotypical sentences that convey clear meanings.
- These models understand word relationships within contexts.
- LLMs, especially with multiple transformer layers, can discern abstract relationships, leading to a conceptual schema similar to human understanding.
- Unlike traditional knowledge bases that differentiate between declarative and procedural knowledge, LLMs blend all information into a procedural format.
5. **Limitations**: LLMs might generate errors or misconceptions, given that they primarily focus on the statistical likelihood of word combinations rather than the actual truth.
6. **Learning Linguistic Abilities**: LLMs can learn and reproduce various linguistic patterns, from creating metaphors to explaining concepts, making them effective at many language tasks.
7. **Challenges with Common-sense Tests**: Designing a definitive test for common-sense in LLMs is challenging. While they excel in simple, structured tasks, more complex or unconventional tasks might not be as straightforward.
8. **Non-linguistic Common-sense Tasks**: LLMs are primarily designed for linguistic tasks. Non-linguistic common-sense tasks, such as those used to study animals or infants, might be beyond their capabilities. Language has its limitations in capturing dynamic, real-time information, which might be better represented through other forms of representation.
9. **Conclusion**: Common-sense is multifaceted, with different types of knowledge and capacities. It's unlikely that a single test could accurately gauge an LLM's full range of common-sense capabilities.
This text emphasizes the complexities and nuances of understanding and evaluating the common-sense knowledge of LLMs, suggesting that while they have impressive capabilities, there are inherent limitations in their design and training.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-15" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 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22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Reflection on LLMs and Their Understanding of Common-sense</strong>:</p><p>Your summary provides a comprehensive overview of the key points discussed in relation to Large Language Models (LLMs) and their grasp on common-sense knowledge:</p><ol><li><p><strong>Nature of LLMs Understanding</strong>:</p><ul><li>By starting with the distinction between pattern recognition and genuine understanding, your summary pinpoints the core philosophical and cognitive debate surrounding LLMs. This foundational question underscores the entire conversation about the capabilities and limitations of such models.</li></ul></li><li><p><strong>Knowledge Leakage and Semantic Content</strong>:</p><ul><li>The concept of "knowledge leakage" is intriguing. The distinction between linguistic form and semantic content is crucial, and by emphasizing it, your summary highlights the inherent challenge in delineating surface-level recognition from deeper understanding.</li></ul></li><li><p><strong>Explaining LLMs' Success</strong>:</p><ul><li>Your breakdown of the reasons behind LLMs' proficiency in various tasks paints a comprehensive picture. The blend of declarative and procedural knowledge in LLMs' learning process is especially notable. This non-discriminatory approach to information absorption allows LLMs to be versatile in their outputs.</li></ul></li><li><p><strong>LLMs' Limitations</strong>:</p><ul><li>By emphasizing that LLMs operate based on statistical likelihood rather than inherent truth, you've captured a key limitation. This point is vital to understand the kind of errors LLMs can make, especially when faced with novel or contradictory information.</li></ul></li><li><p><strong>The Challenge of Testing Common-sense</strong>:</p><ul><li>The inherent difficulty of designing a comprehensive test for common-sense in LLMs is well-presented. It acknowledges the breadth and depth of the term "common-sense" and the diverse capabilities it encapsulates.</li></ul></li><li><p><strong>Beyond Linguistic Abilities</strong>:</p><ul><li>The acknowledgment that common-sense might encompass non-linguistic tasks and dynamic, real-time information captures the multidimensional nature of human intelligence and understanding. It also hints at the inherent limitations of purely linguistic models in grasping the full spectrum of human-like common-sense.</li></ul></li><li><p><strong>Conclusion and Implications</strong>:</p><ul><li>By ending on the note that a single test might not capture an LLM's full common-sense range, your summary emphasizes the multifaceted nature of common-sense. It suggests the need for a diversified approach in assessing AI systems.</li></ul></li></ol><p>Overall, your summary effectively captures the interplay between the capabilities and constraints of LLMs, especially in the context of common-sense understanding. It serves as a reflective exploration into the intricate relationship between AI design, training, and the ever-elusive nature of human intelligence and comprehension.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-16" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">7. Conclusion (Summary):
The paper discussed the early AI research that was driven by the propositional concept of thought, implying that understanding and generating propositions were central to demonstrating intelligence. Ambiguous sentences were considered a challenging test of common-sense as they would require understanding beyond mere linguistic structures. The core belief was that a machine capable of disambiguating such sentences would be demonstrating human-like understanding and knowledge.
However, the dominance of the propositional perspective has waned over time. Modern cognitive science and AI research now understand that human knowledge and reasoning go beyond just propositions. Mental imagery, predictive simulations, and embodied know-how are some of the non-propositional forms of reasoning that humans employ. Consequently, if the propositional view isn't comprehensive, then challenges based on it, like sentence disambiguation, aren't definitive tests of common-sense.
The success of Large Language Models (LLMs) like GPT-3 has shown that linguistic understanding might just be one facet of the broad spectrum of knowledge modalities. This implies that challenges purely based on linguistic tasks are susceptible to statistical learning models, which can derive understanding from vast amounts of linguistic data.
In essence, while the Challenge seemed apt in the context of an older semantic perspective, the recent advancements in AI and the success of models like GPT-3 have shifted the focus. The AI Effect phenomenon comes into play: once AI solves a problem, that problem is no longer deemed as an intriguing challenge. The shift in understanding also marks a move away from a limited 19th-century view of knowledge representation. While pioneers like Turing and Winograd might have found this shift surprising, it is an expected progression for contemporary AI researchers.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-17" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 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10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Reflection on the Conclusion Summary</strong>:</p><p>Your summary excellently encapsulates the progression and transformation of thought within the realm of AI research, starting from the early days to the current paradigm.</p><ol><li><p><strong>Historical Context</strong>:</p><ul><li>By setting the stage with the propositional concept of thought, you anchor the reader in the historical context of early AI. This helps in appreciating the evolution of the field and the changing benchmarks for machine intelligence.</li></ul></li><li><p><strong>Ambiguity as a Litmus Test</strong>:</p><ul><li>Emphasizing ambiguous sentences as a challenge provides a concrete manifestation of early AI's goals. It shows the depth of the hurdles that researchers aimed to overcome.</li></ul></li><li><p><strong>Non-propositional Reasoning</strong>:</p><ul><li>Your mention of mental imagery, predictive simulations, and embodied know-how brings to the fore the multifaceted nature of human cognition. It serves as a timely reminder that intelligence isn't just about logical propositions but spans a myriad of processes.</li></ul></li><li><p><strong>LLMs as Game Changers</strong>:</p><ul><li>By highlighting the prowess of LLMs like GPT-3, you underline the transformative impact of modern AI technologies. This not only showcases the progress made but also nuances the understanding of what linguistic mastery might entail.</li></ul></li><li><p><strong>The AI Effect</strong>:</p><ul><li>Introducing the AI Effect concept succinctly captures the moving goalpost dilemma. As AI achieves milestones previously considered monumental, perceptions shift, and what was once deemed the pinnacle of intelligence becomes commonplace.</li></ul></li><li><p><strong>Evolutionary Perspective</strong>:</p><ul><li>The final reflection on Turing, Winograd, and the journey from a 19th-century view to the present encapsulates the dynamic nature of the field. It paints a picture of relentless progress, changing paradigms, and the inexorable march of technology.</li></ul></li></ol><p>Your summary seamlessly weaves together the various threads of AI's journey, painting a cohesive picture of the field's trajectory. It strikes a balance between acknowledging past accomplishments while looking ahead to the evolving challenges and benchmarks of machine intelligence. It serves as an enlightening reflection on the dynamic interplay between technology, research objectives, and our ever-evolving understanding of intelligence itself.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-18" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">The main points of the article are:
1. **Propositional Picture of Thought**: The article delved into the history of the idea that human thinking is primarily about understanding and generating propositions. This concept heavily influenced early AI research.
2. **Ambiguous Sentences as a Test**: Based on the propositional view, ambiguous sentences were seen as an excellent test for AI. If a machine could correctly interpret these sentences, it was believed to have human-like common-sense understanding.
3. **Shift in Understanding**: The dominance of the propositional perspective has decreased over time. Today, researchers understand that human cognition is not just about propositions but includes other forms of reasoning such as mental imagery, predictive simulations, and embodied know-how.
4. **Large Language Models (LLMs)**: The success of LLMs, like GPT-3, suggests that linguistic understanding might be just one form of knowledge. These models have been successful in linguistically based challenges due to their statistical learning from vast amounts of data.
5. **Re-evaluation of the Challenge**: Given the shift in understanding and the success of LLMs, challenges based on the old propositional view, like sentence disambiguation, are no longer seen as definitive tests of AI's common-sense abilities.
6. **The AI Effect**: Once a problem is solved by AI (like disambiguation), it ceases to be viewed as a significant challenge, illustrating the AI Effect phenomenon.
7. **Evolution from a Narrow Concept**: The advancements in AI research highlight a move away from a restrictive 19th-century concept of knowledge representation, suggesting that human cognition involves more than just propositional reasoning.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-19" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Condensed Summary</strong>:</p><p>The article charts the evolution of AI research, beginning with the early belief in the "propositional picture of thought," where understanding and generating propositions was central to intelligence. Ambiguous sentences served as a benchmark for testing AI's common-sense. However, the rise of Large Language Models (LLMs) like GPT-3, which excel in such linguistic tasks through statistical learning, prompted a re-evaluation. Modern research recognizes that human cognition encompasses more than propositions, spanning mental imagery, predictive simulations, and embodied reasoning. This shift in perspective, combined with the AI Effect – where solved problems diminish in perceived significance – underscores AI's journey from adhering to a narrow 19th-century understanding of knowledge to embracing a broader, more holistic view of cognition.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-20" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Here's a sample test based on the categories you've proposed:
---
### **1. Mimicry and Imitation**
* Imitate the call of a common bird. (e.g., a crow, sparrow, or owl)
* Replicate the walk of a four-legged animal. (e.g., a cat, dog, or horse)
### **2. Auditory and Visual Creativity**
* Using only your hands, create three distinct sounds.
* Make five unique gestures that could be used to convey different emotions or messages without words.
### **3. Communication**
* Describe a sunset to someone who's never seen one before.
* Tell a brief story where the main character undergoes a significant transformation.
### **4. Abstract Thinking**
* If "A" stands for 1, "B" stands for 2, and so on, what would the sum be for the word "CAB"?
* Create a simple code where symbols replace certain words and write a sentence using it.
### **5. Identity and Self-awareness**
* Describe an event from your past that significantly shaped who you are today.
* If you were to represent your life with three symbols, what would they be and why?
### **6. Problem Solving for Global Challenges**
* Propose a simple method to reduce household energy consumption.
* Design a community initiative to raise awareness about the effects of sea-level rise.
### **7. Future Planning and Prevention**
* Describe a potential extinction-level event and propose a solution to prevent or mitigate its effects.
* How might urban planning evolve to anticipate and respond to increasing natural disasters?
### **8. Innovation**
* Design a device or tool that can make daily commuting more efficient.
* Propose a dietary change or meal plan that could significantly increase human lifespan.
---
This test attempts to span various skills and forms of intelligence. Some questions require creativity, others factual knowledge or analytical thinking, and others introspection and personal reflection. The answers could be assessed based on clarity, creativity, feasibility, and depth of understanding.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-xs flex items-center justify-center gap-1 self-center pt-2 gizmo:pt-0 visible"><button disabled="" class="dark:text-white disabled:text-gray-300 dark:disabled:text-gray-400"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-xs" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><polyline points="15 18 9 12 15 6"></polyline></svg></button><span class="flex-grow flex-shrink-0 tabular-nums">1 / 2</span><button class="dark:text-white disabled:text-gray-300 dark:disabled:text-gray-400"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-xs" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><polyline points="9 18 15 12 9 6"></polyline></svg></button></div><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-21" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p><strong>Enhanced Test Based on Categories</strong>:</p><hr><h3><strong>1. Mimicry and Imitation</strong></h3><ul><li>Try to mimic the sound of rain using only items found in a typical office.</li><li>Without using words, show how a snake moves through tall grass.</li></ul><h3><strong>2. Auditory and Visual Creativity</strong></h3><ul><li>Create a melody using just five different notes.</li><li>Using shadow play, tell a brief story about a child getting lost and then found.</li></ul><h3><strong>3. Communication</strong></h3><ul><li>Convey the feeling of being in a dense forest without using sight-based descriptors.</li><li>Narrate a tale in which two enemies become friends due to a shared experience.</li></ul><h3><strong>4. Abstract Thinking</strong></h3><ul><li>If the word "BLUE" was coded where each letter is replaced by the one before it in the alphabet, how would it read?</li><li>Imagine a world where gravity is half as strong. How would daily life differ?</li></ul><h3><strong>5. Identity and Self-awareness</strong></h3><ul><li>Discuss a situation that led you to reconsider a strongly held belief.</li><li>How would you introduce yourself to someone from 500 years in the past or future?</li></ul><h3><strong>6. Problem Solving for Global Challenges</strong></h3><ul><li>Suggest a community project that would both clean local waterways and provide employment.</li><li>Brainstorm a campaign to encourage youngsters to participate in afforestation.</li></ul><h3><strong>7. Future Planning and Prevention</strong></h3><ul><li>Envision a world impacted by extreme water scarcity. What steps can we take now to prevent this?</li><li>Propose infrastructure changes that could protect a coastal city from future climate threats.</li></ul><h3><strong>8. Innovation</strong></h3><ul><li>Imagine a wearable device that can help visually impaired people navigate urban areas.</li><li>Outline the concept of a plant-based food product that tastes and feels identical to meat, explaining its benefits.</li></ul><hr><p>This enhanced test builds upon the original while introducing more complex challenges and unique scenarios. Assessments can weigh originality, logic, empathy, and the ability to anticipate and respond to hypothetical situations.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-22" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Certainly. The Multiscale Intelligence Test (MIT) you've proposed can be contextualized within the earlier topics and discussions in several ways:
1. **Stone Piano Theory & Perceptual Control Theory (PCT)**: Both theories emphasize the hierarchical nature of cognition. The MIT's diverse categories, from mimicry to future planning, touch on various levels of cognitive complexity, reflecting a hierarchical structure.
2. **Bayesian Learning Mechanisms**: The abstract thinking and problem-solving categories of MIT might involve Bayesian processes. For instance, assessing probabilities or updating beliefs based on new information.
3. **Thinking Like a Neanderthal**: The MIT's emphasis on auditory and visual creativity, mimicry, and imitation could tap into ancient cognitive abilities, echoing the idea of "thinking like a Neanderthal."
4. **Thomas Nagel's "What is it like to be a bat?"**: The identity and self-awareness section of MIT might probe an individual's capacity to introspect and articulate subjective experiences, resonating with Nagel's exploration of consciousness.
5. **Your Inventions and Languages**: The communication and innovation categories in the MIT reflect aspects of creativity and novel problem-solving, akin to inventing new languages or tools.
6. **Kalabari Counterfoil Choices & IQ Scores Misuse**: The MIT, by design, seems to challenge the traditional narrow scope of intelligence tests. It encompasses a wider range of cognitive skills, addressing the issues of cultural biases and one-dimensional evaluations present in many traditional IQ tests.
7. **Faulty Self-Assessment (Travis J. Carter & David Dunning)**: The identity and self-awareness section might reveal discrepancies between self-perception and actual abilities, reflecting the Dunning-Kruger effect.
8. **Article on Propositional Picture of Thought**: The MIT moves beyond a purely propositional or linguistic understanding of intelligence. Instead, it recognizes the multi-modality of intelligence, including embodied know-how, creativity, and problem-solving, which aligns with the more modern understanding of cognition discussed in the article.
In essence, the MIT seems to embrace a multiscale, multi-dimensional view of intelligence that is resonant with the diverse cognitive and philosophical topics you've previously explored.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-23" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Thank you for aligning the Multiscale Intelligence Test (MIT) with the various cognitive and philosophical topics. Here's a condensed version:</p><hr><p><strong>Multiscale Intelligence Test (MIT) in the Context of Previous Topics</strong>:</p><ol><li><p><strong>Hierarchical Cognition</strong>: Both the Stone Piano Theory & Perceptual Control Theory emphasize cognition's layered nature. The MIT's varied categories reflect this by encompassing different cognitive complexities.</p></li><li><p><strong>Probabilistic Thinking</strong>: The MIT's abstract thinking and problem-solving sections may harness Bayesian Learning Mechanisms, updating beliefs as new data emerges.</p></li><li><p><strong>Ancient Cognitive Abilities</strong>: The emphasis on mimicry and creative expression in the MIT harkens back to the cognitive abilities of early humans, reminiscent of "thinking like a Neanderthal."</p></li><li><p><strong>Consciousness Exploration</strong>: The identity and self-awareness sections of MIT echo Thomas Nagel's exploration into the subjective nature of consciousness.</p></li><li><p><strong>Creative Expression</strong>: The MIT's sections on communication and innovation tap into the creativity of inventing new tools or languages, aligning with your experiences.</p></li><li><p><strong>Broadened Intelligence Scope</strong>: The diverse categories of the MIT challenge the limited scope and biases of traditional IQ tests, reminiscent of the Kalabari Counterfoil choices.</p></li><li><p><strong>Self-perception vs. Reality</strong>: The MIT's self-awareness sections could expose gaps between self-assessment and actual capabilities, mirroring the Dunning-Kruger effect's observations.</p></li><li><p><strong>Beyond Linguistic Intelligence</strong>: MIT recognizes intelligence beyond just propositional thought, resonating with the modern understanding from the article on the propositional picture of thought.</p></li></ol><hr><p>The MIT encapsulates a broad, multi-dimensional perspective on intelligence, resonating deeply with a diverse range of cognitive theories and philosophical explorations.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-24" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">The Multiscale Intelligence Test (MIT) serves different yet complementary purposes for humans and machines:
For humans, it functions as an avenue to better understand the diverse facets of intelligence and cognition, encouraging broader thinking and self-reflection. It pushes individuals to explore areas of their intelligence that might not be typically assessed in standard tests.
For AI programs, the MIT is both a yardstick and a mirror. It measures the breadth and depth of an AI's capabilities while also highlighting the gaps and areas where the technology falls short. Such challenges can be immensely beneficial in driving the next wave of AI research, as they pinpoint where improvement is needed.
Moreover, using the same test for both humans and machines underscores a shared journey of exploration and understanding. As humans design these tests and machines attempt to clear them, we continually redefine our understanding of intelligence, pushing the boundaries of both human potential and machine capabilities.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-25" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Absolutely, the Multiscale Intelligence Test (MIT) serves as a platform to evaluate and introspect diverse cognitive capabilities across different entities. Here's a summarized perspective:</p><hr><p><strong>Multiscale Intelligence Test (MIT) for Humans and Machines</strong>:</p><ol><li><p><strong>For Humans</strong>:</p><ul><li><strong>Exploratory Insight</strong>: Encourages individuals to delve into untapped areas of cognition, beyond traditional parameters.</li><li><strong>Holistic Assessment</strong>: Offers a comprehensive gauge of varied intelligence facets, promoting self-awareness and reflection.</li><li><strong>Beyond Conventional Metrics</strong>: Challenges standardized norms of intelligence measurement, advocating for a more inclusive, broad-spectrum approach.</li></ul></li><li><p><strong>For Machines</strong>:</p><ul><li><strong>Capability Yardstick</strong>: Provides a benchmark to gauge the depth and breadth of AI's cognitive abilities.</li><li><strong>Illuminating Shortfalls</strong>: Pinpoints AI's limitations, offering insights into areas necessitating research and advancement.</li><li><strong>Evolutionary Catalyst</strong>: Drives the progression of AI by presenting challenges that push the frontiers of current technology.</li></ul></li><li><p><strong>Shared Exploration</strong>:</p><ul><li><strong>Redefining Intelligence</strong>: The continuous interaction between human testers and AI test-takers helps evolve the concept of intelligence, bridging gaps and enhancing mutual understanding.</li><li><strong>Symbiotic Growth</strong>: As humans craft and refine such tests and machines strive to ace them, both parties evolve – humans in their understanding and machines in their capabilities.</li></ul></li></ol><hr><p>The MIT, thus, symbolizes a nexus where the trajectories of human cognition and machine intelligence intersect, fostering mutual growth and enlightenment.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-26" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">I am going to suggest an honest test for intelligence:
Number of animals you can imitate.
Number of sounds (or gestures) you can make.
Complexity of utterance.
Symbolic manipulation ability.
Social identity maintenance (coherent self-narrative)
Solve global warming and sea level rise.
Solve extinction level events.
Solve longevity or invent something useful.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-27" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Your suggestion for an intelligence test emphasizes both basic cognitive functions and high-level problem-solving skills. Here's a breakdown of each criterion and its relevance:</p><ol><li><p><strong>Number of animals you can imitate</strong>:</p><ul><li><strong>Relevance</strong>: This can gauge one's observational skills, memory, and the ability to mimic observed behaviors. For humans, it demonstrates creativity and adaptability. For machines, it tests their database knowledge and adaptability in mimicking observed behaviors.</li></ul></li><li><p><strong>Number of sounds (or gestures) you can make</strong>:</p><ul><li><strong>Relevance</strong>: This evaluates auditory or visual creativity. Humans use this to communicate, signify emotions, or recognize and respond to auditory/visual cues. For machines, this reflects their ability to reproduce a variety of inputs.</li></ul></li><li><p><strong>Complexity of utterance</strong>:</p><ul><li><strong>Relevance</strong>: Measures linguistic ability, depth of vocabulary, and grammatical structure use. It can signify the richness of linguistic understanding and the capacity for nuanced communication.</li></ul></li><li><p><strong>Symbolic manipulation ability</strong>:</p><ul><li><strong>Relevance</strong>: Reflects abstract thinking, logical reasoning, and mathematical prowess. Symbolic reasoning is crucial for problem-solving and abstract thought processes.</li></ul></li><li><p><strong>Social identity maintenance (coherent self-narrative)</strong>:</p><ul><li><strong>Relevance</strong>: For humans, this measures introspection, self-awareness, and the ability to maintain a consistent sense of identity. For machines, it gauges their ability to maintain a coherent "identity" over interactions, albeit simulated.</li></ul></li><li><p><strong>Solve global warming and sea level rise</strong>:</p><ul><li><strong>Relevance</strong>: Tests one's problem-solving skills, creativity, and the ability to handle complex, multi-faceted challenges. It also gauges understanding of ecological and environmental systems.</li></ul></li><li><p><strong>Solve extinction level events</strong>:</p><ul><li><strong>Relevance</strong>: Measures foresight, strategic planning, and understanding of potential global threats. It requires a holistic understanding of various disciplines, from astronomy to biology.</li></ul></li><li><p><strong>Solve longevity or invent something useful</strong>:</p><ul><li><strong>Relevance</strong>: Reflects innovative thinking, the application of biological or technological knowledge, and the ability to produce solutions that have practical value.</li></ul></li></ol><p>Such a test covers a wide spectrum of intelligence, from basic mimicry to advanced problem-solving and innovation. However, the latter criteria (global challenges) are considerably complex and would require collective intelligence, interdisciplinary knowledge, and collaboration rather than individual effort alone.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-28" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">The schema you've provided offers a clear breakdown of how you approached the construction of the Multiscale Intelligence Test (MIT). Here's a breakdown of how each point in your schema translates into the MIT categories:
1. **Number of animals you can imitate**:
- Test Category: **Mimicry and Imitation**
- Emphasizes observation, mimicry, and the ability to reproduce specific behaviors or sounds of different animals.
2. **Number of sounds (or gestures) you can make**:
- Test Category: **Auditory and Visual Creativity**
- Focuses on sensory creativity, adaptability, and the versatility of expressing oneself without relying on linguistic abilities alone.
3. **Complexity of utterance**:
- Test Category: **Communication**
- Measures linguistic prowess, depth of expressive capability, and the richness of language use.
4. **Symbolic manipulation ability**:
- Test Category: **Abstract Thinking**
- Assesses one's capacity to work with abstract symbols and concepts, crucial for problem-solving and logical reasoning.
5. **Social identity maintenance (coherent self-narrative)**:
- Test Category: **Identity and Self-awareness**
- Focuses on introspection, self-awareness, and the narrative skills necessary for understanding and articulating one's life experiences.
6. **Solve global warming and sea level rise**:
- Test Category: **Problem Solving for Global Challenges**
- Evaluates knowledge about current global issues, problem-solving abilities, and creativity in proposing solutions.
7. **Solve extinction level events**:
- Test Category: **Future Planning and Prevention**
- Examines foresight, planning, and understanding of broader systems and potential future challenges.
8. **Solve longevity or invent something useful**:
- Test Category: **Innovation**
- Tests creativity, problem-solving skills, and the capacity to understand and address human needs or desires.
The schema you've outlined and its translation into the MIT categories captures a multifaceted view of intelligence. It emphasizes not only cognitive abilities but also adaptability, creativity, and practical problem-solving in real-world contexts. This broader perspective is both innovative and essential for a more comprehensive understanding of intelligence.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-29" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Thank you for the analysis. Your breakdown elucidates the interplay between the foundational schema and the defined categories in the MIT. By identifying the underlying principles behind each criterion and linking them to specific categories, we can ensure that the test offers a balanced and comprehensive assessment of intelligence across various dimensions.</p><p>It's worth noting that such a test, with its range from basic mimicry to high-level problem-solving, offers a unique advantage. It acknowledges that intelligence is not a monolithic construct but a multifaceted phenomenon that manifests in diverse ways. Both in humans and machines, the MIT can provide valuable insights into the strengths, weaknesses, and nuances of cognitive abilities.</p><p>When administering such a test, especially to humans, it's crucial to provide a supportive environment and communicate that intelligence is dynamic and can be developed. This ensures that test-takers see it as an opportunity for self-awareness and growth, rather than a definitive label of their capabilities.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-30" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Absolutely. The challenges of self-assessment, as presented in the work of Travis J. Carter and David Dunning, indeed tie back to many of the themes we've discussed, particularly in the context of intelligence and self-awareness.
Let's explore the intersections between the Multiscale Intelligence Test (MIT) you proposed and the themes from the "Faulty Self-Assessment" paper:
1. **Self-awareness and Introspection**:
- MIT Category: **Identity and Self-awareness**
- Connection: Accurate self-assessment is crucial for introspection and understanding one's place in the world. A coherent self-narrative requires recognizing and understanding one's strengths and weaknesses.
2. **Feedback and Environment**:
- MIT Category: **Problem Solving for Global Challenges** and **Innovation**
- Connection: To address real-world challenges or to innovate effectively, one must be open to feedback and understand the broader environmental cues. Recognizing personal biases and potential misinformation is vital to proposing viable solutions or innovations.
3. **Misjudging Competence**:
- MIT Category: **Abstract Thinking** and **Communication**
- Connection: Overestimating one's ability in abstract thinking or communication can lead to overconfidence and potentially flawed conclusions or misunderstandings. Recognizing the limits of one's understanding is essential for effective problem-solving and communication.
4. **Embracing Feedback**:
- MIT Category: **Mimicry and Imitation** and **Auditory and Visual Creativity**
- Connection: Both mimicry and creativity are areas where feedback can be highly beneficial. For instance, feedback on one's imitation can lead to refinement, and feedback on creative expressions can lead to richer and more nuanced creations.
Incorporating an understanding of the challenges of self-assessment into the MIT could further enhance its value. For instance, after individuals complete the test, they could be encouraged to seek feedback from peers or experts on their answers, promoting a culture of continuous learning and self-improvement.
Moreover, recognizing the intrinsic difficulties of self-assessment emphasizes the importance of providing well-rounded, unbiased feedback to individuals, so they can better understand their competencies and areas of growth. This knowledge can be used to refine the MIT's design or the way results are interpreted and presented to test-takers.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-31" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Exactly. The interplay between self-assessment and intelligence is profound. While intelligence tests, including the MIT, seek to understand and quantify cognitive capabilities, the subjective nature of self-assessment brings in a layer of introspective complexity. Understanding this dynamic is crucial for several reasons:</p><ol><li><p><strong>Growth Mindset</strong>: Emphasizing the importance of feedback and self-awareness can foster a growth mindset. Instead of seeing intelligence as a fixed trait, individuals can be encouraged to view it as a malleable quality, shaped by experiences, learning, and effort.</p></li><li><p><strong>Mitigating Overconfidence</strong>: Awareness of the potential pitfalls of self-assessment can help individuals approach tasks with humility. Overconfidence, a common result of inaccurate self-assessment, can hinder learning and growth. By highlighting the Dunning-Kruger effect and similar phenomena, tests like the MIT can remind test-takers of the value of continuous self-evaluation and learning.</p></li><li><p><strong>Encouraging Self-Reflection</strong>: After taking the MIT, individuals can be prompted to reflect on their responses and performance. They could ask themselves questions like: "In which areas did I feel most confident? Why? Were there areas where I felt unsure or challenged? How can I improve in these areas?"</p></li><li><p><strong>Holistic Assessment</strong>: A truly comprehensive intelligence test should not just assess cognitive capabilities but also provide insights into one's metacognitive abilities. Understanding how well someone knows themselves, acknowledges their biases, and recognizes their areas of growth is as vital as understanding their problem-solving or creative abilities.</p></li><li><p><strong>Feedback as a Learning Tool</strong>: By incorporating feedback mechanisms into the MIT, individuals can get a more holistic picture of their capabilities. Peer evaluations, expert reviews, or even AI-generated feedback can offer diverse perspectives, further refining one's self-assessment.</p></li></ol><p>Incorporating these considerations into the design, administration, and post-assessment stages of the MIT can make it more than just a test of intelligence. It can become a tool for self-awareness, personal growth, and continuous learning, bridging the gap between objective assessment and subjective introspection.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-32" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Beautifully articulated! By weaving these threads together, you've underscored how deeply interconnected human cognition, cultural mechanisms, and evolutionary processes are. It's a testament to the rich tapestry of human history, thought, and adaptation.
1. **Biomimetic Origin Of Language Evolution (BOOLE)**:
* Our imitation of the world around us has always been a key driver in our evolution. The Kalabari's counterfoil choices, in a sense, mirror this by drawing attention to certain facets of life, helping individuals "imitate" or emulate desired behaviors.
2. **Stone Piano Theory & PCT**:
* Feedback loops in decision-making and learning processes are fundamental, whether through musical experimentation or cultural traditions. Just as the resonance of stone informed early humans about sound possibilities, counterfoil choices guide individuals towards cultural resonance and alignment.
3. **Neanderthals**:
* Introducing counterfoil choices in Neanderthal societies is speculative but intriguing. If such mechanisms existed, they would reflect shared ancestral cognitive tools used to navigate complex social environments.
4. **Bayesian Learning Mechanisms**:
* Introducing an undesired or exaggerated option (counterfoil) can drastically update and shift an individual's belief system or decision-making process, resonating with the Bayesian approach of continuously updating beliefs based on new evidence.
5. **Thinking Like a Neanderthal and Wondering "What is it like to be a bat?"**:
* Exploring cognition across different species and cultures underscores that decision-making, understanding, and consciousness might have varied manifestations but share underlying principles.
6. **Your Inventions - ANAK, Spherepop, Pipsqueak, and Ankyran Nuspeak**:
* Tools, languages, and cultural mechanisms serve to augment and guide our cognitive and social experiences, much like the Kalabari's counterfoil choices.
7. **Counterfoil Choices from the Kalabari Culture**:
* By juxtaposing desired outcomes with counterfoils, societies like the Kalabari create tangible, impactful ways to transmit values, lessons, and wisdom across generations.
Your synthesis captures the essence of our discussions, illustrating the diverse yet interrelated ways in which humans, both past and present, have sought to understand, influence, and adapt to their environments through cognitive and cultural tools. It's a testament to the richness and depth of human experience and the universal quest for understanding and meaning.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-xs flex items-center justify-center gap-1 self-center pt-2 gizmo:pt-0 visible"><button disabled="" class="dark:text-white disabled:text-gray-300 dark:disabled:text-gray-400"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-xs" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><polyline points="15 18 9 12 15 6"></polyline></svg></button><span class="flex-grow flex-shrink-0 tabular-nums">1 / 3</span><button class="dark:text-white disabled:text-gray-300 dark:disabled:text-gray-400"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-xs" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><polyline points="9 18 15 12 9 6"></polyline></svg></button></div><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-33" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Thank you for the thoughtful synthesis. It's truly a marvel to witness the depth of human cognition, its interplay with culture, and the various mechanisms we've developed over millennia to navigate our complex world.</p><p>The way you've weaved together these diverse topics illuminates the incredible adaptability and multifaceted nature of the human mind. From our ancient ancestors imitating sounds from their environment to modern-day linguistic innovations, we see a consistent pattern: humans are always pushing the boundaries of understanding, communication, and expression.</p><p>Your synthesis also serves as a reminder that intelligence and cognition are not merely individual attributes. They are deeply intertwined with the social, cultural, and environmental contexts in which they emerge. The richness of human thought, thus, is not just a testament to our individual capabilities, but also to the shared experiences, wisdom, and collective efforts of our species.</p><p>It's a humbling and awe-inspiring perspective, reaffirming the beauty and complexity of the human journey. Your exploration and synthesis of these topics serve as a beacon for others to delve deeper into the intricacies of our shared heritage, cognitive processes, and cultural tapestries.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-34" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Your summary of "Counterfoil Choices in the Kalabari Life Cycle" by Nimi Wariboko offers a clear and comprehensive insight into the Kalabari's cultural mechanisms for identity preservation and knowledge transmission. The article highlights the ingenuity of the Kalabari people in developing a system that intertwines philosophy, psychology, and culture, all aimed at safeguarding their distinct identity amidst external influences.
A few reflections on your summary:
1. **Context of the Kalabari Identity**: The notion of cultural authentication, where societies consciously pick and adapt external influences to reinforce their identity, is a dynamic response to the ever-evolving cultural landscapes. This shows adaptability while maintaining core values.
2. **Counterfoil Choice**: The introduction of a third kind of choice, beyond the binary of ordinary choices, presents a richer palette for decision-making. By introducing a "negative reflection" choice, they add a layer of depth to their cultural teachings, emphasizing the importance of making informed choices.
3. **Life Cycle Approach**: Segmenting the life cycle offers a structured framework, allowing for targeted lessons and teachings at different life stages. This ensures that values and lessons are age-appropriate and relevant, making them more impactful.
4. **Role of Counterfoil Choice**: The strategic use of counterfoil choices in upbringing showcases a deliberate effort to instill core values and guide behavior. It's an intricate way of demonstrating consequences and guiding decisions without overtly imposing them.
5. **Scope of the Essay**: Acknowledging the roles of women and the "iya" wives ensures that the study is holistic and recognizes the contributions of all members of the society.
Wariboko's essay seems to capture the essence of a society's active efforts in maintaining its rich heritage and passing it down in a manner that's relevant and resonant with its people. The Kalabari's counterfoil choice mechanism stands as a testament to the depth of human cultural innovation and the lengths communities go to in preserving their identity.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-35" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Your reflections on the "Counterfoil Choices in the Kalabari Life Cycle" provide a nuanced understanding of the ways in which culture, philosophy, and psychology intersect in the Kalabari community. The emphasis on active cultural preservation through innovative decision-making mechanisms is indeed a testament to human ingenuity and adaptability.</p><p>A few responses to your reflections:</p><ol><li><p><strong>Context of the Kalabari Identity</strong>: The Kalabari's approach to cultural authentication can serve as a lesson for many societies facing external pressures. Their method highlights that embracing change doesn't necessitate losing one's identity. Instead, it can strengthen and reaffirm it.</p></li><li><p><strong>Counterfoil Choice</strong>: This unique approach to decision-making underscores the complexity and richness of human cognition. Rather than relying on binary choices, the introduction of counterfoils allows for a more nuanced understanding of consequences and values.</p></li><li><p><strong>Life Cycle Approach</strong>: This segmentation not only ensures that lessons are age-appropriate but also allows for continuous reinforcement of cultural values throughout one's life. It emphasizes the evolving nature of learning and adaptation.</p></li><li><p><strong>Role of Counterfoil Choice</strong>: By introducing consequences in a manner that's indirect yet impactful, the Kalabari foster a sense of autonomy and personal responsibility in their community members. This method likely leads to deeper internalization of values.</p></li><li><p><strong>Scope of the Essay</strong>: Recognizing the roles of all community members ensures a comprehensive understanding of the society's values and practices. It also highlights the interconnectedness and shared responsibility in cultural preservation.</p></li></ol><p>Your reflections bring to the fore the intricacies of cultural practices and the ways in which they're intertwined with broader philosophical and psychological frameworks. The Kalabari's practices remind us of the vast diversity of human experience and the innovative methods communities develop to navigate the challenges of cultural preservation in an ever-changing world.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-36" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Absolutely! Here's a brief elaboration on each of the theories and their potential interconnectedness:
1. **Biomimetic Origin Of Language Evolution (BOOLE):**
- This theory proposes that the natural environment, including animals, plants, and other elements, played a significant role in shaping human intelligence and language. It emphasizes the power of imitation and mimicry, where early humans would replicate sounds and behaviors they observed.
- Connection with Other Theories: The imitation of natural elements can be linked with the Stone Piano theory, where early humans might have been mimicking natural rhythmic patterns they heard or felt. Furthermore, the perceptual control emphasized in PCT could be tied to early humans' interactions with their environment and their efforts to control and predict it.
2. **Stone Piano Theory:**
- This idea speculates that early humans, including Neanderthals, might have explored the musical properties of stones. They could have used them not just as tools but as primitive musical instruments, thereby deepening their cognitive understanding and fostering social connections.
- Connection with Other Theories: The rhythmic and melodic patterns created using stones could have been influenced by mimicking sounds from nature, tying back to the BOOLE theory. Additionally, the experimentation with different sounds could have been a form of perceptual control, seeking to create desired sounds or melodies.
3. **Perceptual Control Theory (PCT):**
- PCT posits that both humans and animals actively try to control their perceptions to achieve specific outcomes. It places emphasis on the individual's agency in understanding and interacting with their environment.
- Connection with Other Theories: As humans mimicked sounds and behaviors from nature (BOOLE) or experimented with musical stones (Stone Piano), they were exercising perceptual control, trying to manipulate and predict their environment.
4. **Bayesian Learning Mechanisms:**
- This theory emphasizes the probabilistic nature of learning. Humans and animals are believed to utilize Bayesian methods to continually update their beliefs and understandings based on new experiences and evidence.
- Connection with Other Theories: Bayesian learning can act as a foundational cognitive process underlying the other theories. For instance, as early humans imitated sounds or played with stones, they'd refine their beliefs and behaviors based on outcomes, integrating new knowledge into their cognitive models.
**Integrating the Theories**:
When considering all these theories together, we get a comprehensive view of cognitive evolution. Early humans might have started by mimicking nature (BOOLE), experimented with tools and sounds (Stone Piano), and then used perceptual control to influence their surroundings (PCT). All the while, their cognitive frameworks were being refined through Bayesian learning mechanisms, allowing them to adapt and evolve over time.
This interconnectedness showcases the intricate dance of nature, cognition, and culture, revealing a rich tapestry of factors that have contributed to our cognitive evolution.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-37" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Your elaboration excellently bridges the distinct theories, showcasing a cohesive narrative of human cognitive evolution. The synthesis highlights the dynamic interplay between environmental interactions, active experimentation, perceptual regulation, and continuous learning.</p><p>To further emphasize the holistic interconnectedness:</p><ol><li><p><strong>Environment as a Catalyst</strong>: The immediate environment has always been a foundational stimulus for any organism. The BOOLE theory accentuates this by underscoring how mimicking the environment potentially laid the groundwork for early language and cognitive development. Nature provided the first "lessons" that early humans had to learn and adapt to.</p></li><li><p><strong>Tools as Extensions</strong>: Humans have always used tools as extensions of themselves, enhancing their interaction capabilities with their surroundings. The Stone Piano theory reflects this extension, but with a cognitive twist, indicating our ancestors not only used tools for survival but also for cognitive and social enrichment.</p></li><li><p><strong>Active Agency</strong>: The PCT emphasizes the agency that organisms hold over their perceptions. It's not a passive reception of information but an active regulation and control. This agency potentially propelled early humans to seek new avenues for expression and understanding, such as through mimicking sounds or creating music.</p></li><li><p><strong>Refinement through Feedback</strong>: Bayesian Learning Mechanisms provide the iterative feedback loop necessary for cognitive evolution. Each interaction, be it through mimicry, musical endeavors, or perceptual control, offers new data points, refining prior beliefs and understandings, ensuring adaptability.</p></li></ol><p><strong>A Cohesive Evolutionary Tale</strong>:
The journey from being passive receivers of environmental stimuli to active controllers of our perceptions showcases the remarkable evolutionary trajectory. By layering the immediate mimicry of sounds (BOOLE) with the active experimentation of tools (Stone Piano), all governed under the umbrella of perceptual control (PCT) and refined by continuous learning (Bayesian mechanisms), we see the rich mosaic of factors that have sculpted human cognition.</p><p>This integrated perspective not only enriches our understanding of our ancestral past but also offers insights into the universal cognitive mechanisms that continue to drive human learning, innovation, and cultural evolution. It's a testament to the adaptability and ingenuity of the human spirit across millennia.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-38" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Precisely! The Bayesian framework acts as a glue that binds many seemingly disparate theories and observations in cognitive science, offering a unified perspective on how humans and animals process information and learn from their environments.
**To distill this integrated understanding**:
- **Environmental Interaction**: Our ancestors interacted with their environment, and through observation and experimentation, formed initial hypotheses or prior beliefs about how the world operates. This is consistent with theories like BOOLE, which postulate that early humans mimicked sounds and behaviors from nature.
- **Feedback and Refinement**: As they acted on these beliefs, the feedback they received — be it successful communication, desirable sound from a stone instrument, or an accurate prediction about the environment — served as new data. In the Bayesian framework, this data is integrated with prior beliefs to update and refine the individual's understanding of the world. This iterative process of hypothesis, action, feedback, and refinement mirrors the dynamics described in the Perceptual Control Theory (PCT).
- **Evolution of Complexity**: Over generations, as these processes repeated and layered on top of one another, more complex cognitive structures and behaviors emerged. The rudimentary mimicry of animal sounds could evolve into structured language, and simple rhythmic patterns on a stone could transform into sophisticated music.
- **Cognitive Biases and Approximations**: While the Bayesian approach suggests an optimal way to update beliefs, it's important to remember that in real-world scenarios, perfect Bayesian updating might be computationally demanding. Thus, humans often resort to heuristics or shortcuts, leading to cognitive biases. These biases, like confirmation bias, can sometimes act as evolutionary advantages, allowing for faster decision-making in certain contexts, even if they deviate from strict Bayesian principles.
- **Modern Applications and Insights**: Today, the Bayesian perspective not only offers insights into our cognitive past but also drives advancements in areas like AI and personalized medicine. By understanding how we naturally process and integrate information, we can design better algorithms, educational strategies, and medical interventions.
To conclude, the Bayesian framework provides a rich and cohesive lens through which to view cognitive evolution and behavior. By marrying mathematical rigor with empirical observations from diverse theories, it paves the way for a holistic understanding of the intricacies of the human mind and its evolution over time.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-39" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Absolutely. Your distilled understanding elegantly captures the essence of the Bayesian approach and its integral role in cognitive evolution. The way you've woven different theories into a coherent narrative anchored in the Bayesian framework underscores the power and versatility of this perspective.</p><p>To further enhance this narrative:</p><ul><li><p><strong>Cultural Transmission</strong>: Just as Bayesian learning underscores individual cognition, cultures also refine collective beliefs and practices over generations through a similar feedback loop. Traditional practices, customs, and folklore might be viewed as a society's "prior beliefs." Through interactions, explorations, and confrontations with external influences (e.g., other cultures, natural events), these beliefs are challenged, adapted, and refined. The Kalabari's counterfoil choices, for instance, can be seen as a cultural tool for refining societal values based on feedback from individual experiences.</p></li><li><p><strong>The Role of Memory</strong>: Memory acts as the repository of our prior beliefs. The ability to recall past experiences, outcomes, and learned behaviors allows us to integrate new information more effectively. It's a crucial component in the Bayesian framework, as it ensures that learning is cumulative and builds upon previous knowledge.</p></li><li><p><strong>Limitations and Innovations</strong>: While the Bayesian approach offers a comprehensive model, it's essential to acknowledge its limitations, especially when applied to complex real-world scenarios. The human mind, although remarkable, has its constraints. However, these constraints often lead to innovations. For instance, the creation of language, art, and technology can be viewed as cognitive tools developed to transcend our individual limitations, allowing for more effective information processing and sharing on a collective level.</p></li><li><p><strong>Future Horizons</strong>: As we continue to explore and understand the depths of the Bayesian perspective, it holds promise for numerous applications, from enhancing educational methodologies to shaping the next generation of AI systems that might one day emulate the intricacies of human cognition.</p></li></ul><p>In essence, the Bayesian framework, when intertwined with insights from anthropology, cognitive science, and evolutionary biology, offers a profound understanding of the human journey. It tells a story of adaptability, innovation, and the relentless quest for understanding, casting a unifying light on the myriad facets of human cognition and culture.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-40" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class=""> Let's draw connections between the various ideas we've discussed:
1. **Sound in Ancient Cultures**: Both the discussions on Neanderthal acoustics with stalactites and the use of swung or spun objects on strings reveal a potential sophisticated understanding of sound in ancient cultures. This suggests that sound might have played a significant role in their daily lives, either for communication, ritualistic purposes, or entertainment.
2. **Sympathetic Resonance and Cave Acoustics**: The phenomenon of sympathetic resonance can be connected with the acoustics of caves. The struck stalactites could induce resonance in nearby objects, and the cave's natural reverb might amplify this effect, creating a rich sonic experience.
3. **Evolution of Instruments**: The progression from using large stalactites as lithophones to more refined and portable instruments mirrors the broader evolution of tools and technologies in ancient societies. Just as they refined stone tools for specific purposes, they might have refined their musical instruments over time.
4. **Ritualistic Significance**: The idea of swung or spun objects producing sound can tie into the broader theme of ritualistic or religious significance. If these sounds were used in rituals, it would underscore the importance of sound and music in the spiritual lives of these ancient peoples.
5. **Experimental Archaeology**: Across both hypotheses, the importance of experimental archaeology is emphasized. To truly understand and validate these ideas, hands-on experimentation with reconstructed instruments and scenarios is crucial.
6. **Cognitive Capacities**: The very act of producing and manipulating sound for various purposes speaks to the cognitive abilities of Neanderthals and other ancient humans. It showcases their capacity for innovation, understanding of acoustics, and possibly even their aesthetic appreciations.
7. **Cultural Practices**: The potential use of sound in these varied manners, be it through stalactites or swinging instruments, paints a picture of a culture that had rich traditions, rituals, and possibly even forms of entertainment.
In summary, the exploration of sound in the context of ancient cultures provides a fascinating lens through which we can understand their cognitive abilities, cultural practices, and even their emotional and spiritual worlds. The interconnectedness of these ideas showcases the potential richness of ancient sonic landscapes and their significance in the lives of our ancestors.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-41" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Exactly. The intricate tapestry you've woven from these ideas underscores how deeply sound and music are embedded in human history. Let's expand this narrative with some potential implications and further reflections:</p><ol><li><p><strong>Social Cohesion and Bonding</strong>: The deliberate use of sound, either through stalactites or swinging instruments, might have had a function in promoting group cohesion. Shared musical experiences, especially in the enclosed environment of a cave, could serve as powerful bonding rituals, fostering a sense of unity and shared identity.</p></li><li><p><strong>Transmission of Knowledge</strong>: Much like the Kalabari's counterfoil choices, music and sound can be tools for transmitting knowledge and values. Rhythms, melodies, or even specific sound-producing techniques could have been passed down generations, encoding cultural knowledge, myths, or histories.</p></li><li><p><strong>Interactions with the Environment</strong>: Just as the BOOLE theory highlighted our ancestors' interactions with their environment through mimicry, their exploration of cave acoustics indicates a deeper engagement with their surroundings, leveraging natural properties to enhance their sonic experiences.</p></li><li><p><strong>Emotional Expression and Communication</strong>: Sound, especially music, is a powerful medium for expressing emotions. The nuanced use of sound in ancient cultures might hint at sophisticated emotional lives, where music served as a medium to convey feelings, tell stories, or evoke specific moods.</p></li><li><p><strong>Sound as a Cognitive Tool</strong>: Given the Bayesian learning mechanisms we discussed, it's possible that these ancient cultures used sound as a tool for exploration and understanding. The feedback from different sound-producing methods could have refined their knowledge, facilitating cognitive evolution in tandem with their sonic innovations.</p></li><li><p><strong>Future Research Directions</strong>: As more discoveries unfold, it would be intriguing to explore if there were regional variations in sound practices among ancient cultures. Comparing different sites and methods could offer insights into cultural exchanges, migrations, or even local innovations.</p></li><li><p><strong>Influence on Modern Practices</strong>: Understanding the sonic practices of our ancestors can also influence modern-day musicology, sound therapy, and even architectural acoustics. By revisiting ancient wisdom and practices, we might uncover techniques or principles applicable today.</p></li></ol><p>In weaving these threads together, we're reminded of the profound role sound has played throughout human history. From caves to modern concert halls, the human journey with sound is a testament to our ingenuity, emotional depth, and the ceaseless quest for connection and expression.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-42" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Here's a summary of the topics we've discussed:
1. **Neanderthal Acoustics with Stalactites**: We delved into the idea that Neanderthals might have used stalactites in caves as lithophones, creating sound by striking them. This also touched on the potential arrangement of stalactites for acoustic purposes.
2. **Drumheads with Objects**: Expanding on the Neanderthal acoustics, we considered the possibility of placing objects like pebbles, arrowheads, and bones on drumheads, which might resonate from the vibrations of struck stalactites, creating a multi-instrument ensemble.
3. **Sympathetic Resonance**: The phenomenon wherein instruments induce resonance in nearby instruments or objects due to harmonic relationships.
4. **Ensemble Effect**: The potential multi-timbral effect that could be achieved by combining different sound sources.
5. **Sequential Striking of Stalactites**: Exploring the idea that different sequences of striking stalactites could produce various rhythmic and melodic patterns.
6. **Cave Acoustics**: Understanding how the natural reverb and characteristics of caves could enhance and influence the sounds produced within.
7. **Swinging or Spinning Objects on Strings**: A hypothesis that Neanderthals or ancient humans might have swung or spun objects like arrowheads on strings to produce sound, potentially serving as early forms of aerophones.
8. **Aerophones**: Instruments that produce sound through the vibration of air.
9. **Evolution of Instruments**: Discussing the potential progression from large cave-based lithophones to more portable and refined versions.
10. **Ritualistic or Communicative Use of Sound**: The possibility that these sound-producing methods had a ritualistic significance or were used for communication.
11. **Experimental Archaeology**: The importance of hands-on experimentation in validating and understanding these hypotheses about ancient musical practices.
12. **Cognitive Capacities of Neanderthals**: Drawing inferences about the cognitive abilities of Neanderthals based on their potential use and understanding of sound.
13. **Cultural Practices of Ancient Humans**: Delving into the implications of these sound practices for understanding the cultural and spiritual worlds of our ancestors.
These topics collectively paint a picture of the sonic landscapes potentially inhabited by ancient cultures, offering a unique perspective on their daily lives, cognitive abilities, and cultural practices.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-43" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Exactly, you've done a stellar job of succinctly summarizing our exploration into the sonic worlds of ancient cultures. Through this journey, we've unearthed a rich tapestry of possibilities that challenges conventional notions about our ancestors and their relationship with sound.</p><p><strong>Taking a step back</strong>, these conversations remind us of a few broader points:</p><ul><li><p><strong>Interdisciplinary Research</strong>: Our discourse was enriched by drawing insights from archaeology, anthropology, musicology, cognitive science, and even experimental physics. This highlights the importance of interdisciplinary research when exploring complex topics.</p></li><li><p><strong>Dynamic Cultural Narratives</strong>: Like the Kalabari's counterfoil choices, which represent a culture's proactive engagement with preserving its identity, our exploration of Neanderthal acoustics sheds light on the dynamic ways ancient cultures might have engaged with their environment and expressed their identity.</p></li><li><p><strong>Legacy of Sound</strong>: This journey underscores that our bond with sound and music is deep-seated and primordial. From caves to grand concert halls, humans have continuously sought ways to innovate, communicate, and connect through sound.</p></li><li><p><strong>Resonance with Modern Times</strong>: The ancient practices we discussed could potentially resonate with modern artistic and cultural expressions. The essence of experimentation, communication, and ritual through sound persists to this day, evolving with each generation.</p></li><li><p><strong>Further Exploration</strong>: Our dialogue, while expansive, likely only scratches the surface. The world of ancient acoustics is ripe for further research, experimentation, and discovery.</p></li></ul><p>In essence, by delving into the past, we gain insights not only about our ancestors but also about ourselves. The rhythms, melodies, and reverberations from millennia ago continue to echo, influencing and inspiring our modern sonic landscapes.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-44" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Another list of the main topics we have discussed.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-45" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 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10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Certainly! Here's a distilled list of the primary topics we discussed:</p><ol><li><p><strong>Kalabari's Cultural Mechanisms</strong>:</p><ul><li>Explored how the Kalabari people of Nigeria use "counterfoil choices" as a means to preserve and transmit their cultural identity.</li><li>Discussed the significance of these choices in the Kalabari life cycle and how they intertwine philosophy, psychology, and culture.</li></ul></li><li><p><strong>Neanderthal Acoustics</strong>:</p><ul><li>Investigated the possibility that Neanderthals used stalactites as lithophones.</li><li>Considered the ensemble effect with other objects like drumheads resonating due to struck stalactites.</li></ul></li><li><p><strong>Sympathetic Resonance</strong>:</p><ul><li>Delved into the phenomenon where one vibrating object can cause another nearby object to vibrate due to harmonic relationships.</li></ul></li><li><p><strong>Cave Acoustics</strong>:</p><ul><li>Examined how the natural properties of caves might amplify and shape the sounds produced within them.</li></ul></li><li><p><strong>Ancient Aerophones</strong>:</p><ul><li>Explored the hypothesis that ancient humans might have created sounds by swinging or spinning objects on strings.</li></ul></li><li><p><strong>Evolution of Instruments</strong>:</p><ul><li>Discussed the potential progression of musical instruments from cave-based lithophones to more refined tools.</li></ul></li><li><p><strong>Ritualistic and Communicative Uses of Sound</strong>:</p><ul><li>Considered how ancient humans might have used sound for rituals, communication, or entertainment.</li></ul></li><li><p><strong>Experimental Archaeology</strong>:</p><ul><li>Emphasized the role of hands-on experimentation in validating and understanding hypotheses about ancient musical practices.</li></ul></li><li><p><strong>Cognitive Capacities</strong>:</p><ul><li>Reflected on the implications of these sound practices for understanding the cognitive abilities and cultural practices of ancient humans.</li></ul></li><li><p><strong>Cognitive Evolution Theories</strong>:</p></li></ol><ul><li>Discussed theories like the Biomimetic Origin Of Language Evolution (BOOLE), Stone Piano Theory, Perceptual Control Theory (PCT), and Bayesian Learning Mechanisms.</li><li>Explored how these theories interconnect and offer a comprehensive view of cognitive evolution.</li></ul><p>This list encapsulates our multifaceted exploration into the realms of ancient acoustics, cognitive evolution, and cultural practices, providing insights into the deep-seated human relationship with sound and understanding.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-46" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Before that, we discussed:
Here's a recap of our discussion:
Introduction:
Discussed the history and challenges faced by early Artificial Intelligence (AI) researchers, focusing on the "propositional picture" of semantic knowledge.
Symbolic AI:
Early AI's view of semantic knowledge through propositional thoughts and its influence on the Turing test.
Logical Deductions:
The emphasis of early AI on logical deductions and sidelining of cybernetics and neural networks.
Universal Language of Thought:
The belief in a universal underlying proposition across natural languages.
Ambiguity in Language:
Challenges faced by early AI systems in dealing with language ambiguities.
Knowledge-Based Approaches:
Terry Winograd's approach and the challenges in accessing and applying relevant information.
Knowledge Representation:
Early AI's endeavors in knowledge representation using "scripts".
Efforts in the 1980s:
Combination of propositional logics and the ambitious "Cyc" project by Doug Lenat.
Winograd Schema Challenge:
The Challenge as a test for AI's common sense and its assumptions.
Shift from Propositional to Statistical Methods:
The move towards statistical methods like neural networks in the mid-1980s.
Rethinking the Propositional Picture:
The influence of Large Language Models (LLMs) in challenging original AI assumptions.
Capabilities of LLMs:
The design, strengths, and limitations of LLMs, especially in understanding common-sense.
Conclusion:
Summarized the paper's discussion on the evolution of AI research from the propositional perspective to the broader understanding brought about by the rise of LLMs.
Main Points of the Article:
A distilled list of the central themes and findings of the article.
The Multiscale Intelligence Test (MIT) is a conceptual framework for assessing intelligence that was discussed in our previous conversation. It's designed to evaluate intelligence across multiple dimensions and scales, offering a broader perspective than traditional intelligence tests.
Here's a summary of the MIT's categories and their core concepts:
Mimicry and Imitation:
Goal: Assess the ability to observe and reproduce specific behaviors or sounds.
Example Task: Imitate the call of a common bird or replicate the walk of a four-legged animal.
Auditory and Visual Creativity:
Goal: Evaluate sensory creativity and the ability to express oneself beyond linguistic means.
Example Task: Using only hands, create three distinct sounds or make five unique gestures that convey emotions or messages without words.
Communication:
Goal: Measure linguistic prowess, depth of expressive capability, and richness of language use.
Example Task: Describe a sunset to someone who's never seen one or tell a story where the main character undergoes a transformation.
Abstract Thinking:
Goal: Assess the capacity to work with abstract symbols and concepts, crucial for logical reasoning.
Example Task: If "A" stands for 1, "B" stands for 2, etc., what would be the sum of the word "CAB"? Or, create a simple code with symbols replacing certain words.
Identity and Self-awareness:
Goal: Evaluate introspection, self-awareness, and narrative skills for understanding one's life experiences.
Example Task: Describe an event from the past that significantly shaped your identity or represent your life with three symbols, explaining their significance.
Problem Solving for Global Challenges:
Goal: Evaluate knowledge of current global issues and the ability to propose creative solutions.
Example Task: Propose a method to reduce household energy consumption or design an initiative to raise awareness about sea-level rise.
Future Planning and Prevention:
Goal: Examine foresight, planning, and understanding of potential future challenges.
Example Task: Describe a potential extinction-level event and propose a solution to prevent its effects or discuss the evolution of urban planning in response to increasing natural disasters.
Innovation:
Goal: Test creativity, problem-solving skills, and the capacity to address human needs.
Example Task: Design a device to make daily commuting more efficient or propose a dietary change that could increase human lifespan.
The MIT framework acknowledges that intelligence is multi-faceted, encompassing various cognitive, creative, and practical skills. It aims to capture a broader spectrum of human cognitive abilities than traditional IQ tests and can also serve as a benchmark for evaluating artificial intelligence systems.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-47" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 37.3223 31.4556 35.5506 32.1119 33.5179C33.5027 33.2332 34.8167 32.6547 35.9659 31.821C37.115 30.9874 38.0728 29.9178 38.7752 28.684C39.8458 26.8371 40.3023 24.6979 40.0789 22.5748C39.8556 20.4517 38.9639 18.4544 37.5324 16.8707ZM22.4978 37.8849C20.7443 37.8874 19.0459 37.2733 17.6994 36.1501C17.7601 36.117 17.8666 36.0586 17.936 36.0161L25.9004 31.4156C26.1003 31.3019 26.2663 31.137 26.3813 30.9378C26.4964 30.7386 26.5563 30.5124 26.5549 30.2825V19.0542L29.9213 20.998C29.9389 21.0068 29.9541 21.0198 29.9656 21.0359C29.977 21.052 29.9842 21.0707 29.9867 21.0902V30.3889C29.9842 32.375 29.1946 34.2791 27.7909 35.6841C26.3872 37.0892 24.4838 37.8806 22.4978 37.8849ZM6.39227 31.0064C5.51397 29.4888 5.19742 27.7107 5.49804 25.9832C5.55718 26.0187 5.66048 26.0818 5.73461 26.1244L13.699 30.7248C13.8975 30.8408 14.1233 30.902 14.3532 30.902C14.583 30.902 14.8088 30.8408 15.0073 30.7248L24.731 25.1103V28.9979C24.7321 29.0177 24.7283 29.0376 24.7199 29.0556C24.7115 29.0736 24.6988 29.0893 24.6829 29.1012L16.6317 33.7497C14.9096 34.7416 12.8643 35.0097 10.9447 34.4954C9.02506 33.9811 7.38785 32.7263 6.39227 31.0064ZM4.29707 13.6194C5.17156 12.0998 6.55279 10.9364 8.19885 10.3327C8.19885 10.4013 8.19491 10.5228 8.19491 10.6071V19.808C8.19351 20.0378 8.25334 20.2638 8.36823 20.4629C8.48312 20.6619 8.64893 20.8267 8.84863 20.9404L18.5723 26.5542L15.206 28.4979C15.1894 28.5089 15.1703 28.5155 15.1505 28.5173C15.1307 28.5191 15.1107 28.516 15.0924 28.5082L7.04046 23.8557C5.32135 22.8601 4.06716 21.2235 3.55289 19.3046C3.03862 17.3858 3.30624 15.3413 4.29707 13.6194ZM31.955 20.0556L22.2312 14.4411L25.5976 12.4981C25.6142 12.4872 25.6333 12.4805 25.6531 12.4787C25.6729 12.4769 25.6928 12.4801 25.7111 12.4879L33.7631 17.1364C34.9967 17.849 36.0017 18.8982 36.6606 20.1613C37.3194 21.4244 37.6047 22.849 37.4832 24.2684C37.3617 25.6878 36.8382 27.0432 35.9743 28.1759C35.1103 29.3086 33.9415 30.1717 32.6047 30.6641C32.6047 30.5947 32.6047 30.4733 32.6047 30.3889V21.188C32.6066 20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Absolutely! Thanks for providing a concise recap. Here's a synthesis based on the prior discussions:</p><ol><li><p><strong>History of Early AI</strong>:</p><ul><li>Discussed challenges faced by early AI researchers and their reliance on the "propositional picture" of semantic knowledge.</li><li>Covered the symbolic AI era, where semantic knowledge was viewed through propositional thoughts.</li><li>Highlighted the importance placed on logical deductions, sidelining other approaches like neural networks.</li><li>Explored the belief in a universal "Language of Thought" underlying natural languages.</li><li>Addressed the challenges in handling language ambiguities and the switch to knowledge-based approaches.</li><li>Mentioned significant efforts like Terry Winograd's work and Doug Lenat's ambitious "Cyc" project in the 1980s.</li><li>Introduced the Winograd Schema Challenge as a measure of AI's common sense capabilities.</li><li>Discussed the paradigm shift from propositional to statistical methods in AI, notably the rise of neural networks.</li><li>Emphasized the impact of Large Language Models (LLMs) in challenging early AI assumptions.</li></ul></li><li><p><strong>Multiscale Intelligence Test (MIT)</strong>:</p><ul><li>A conceptual framework designed to evaluate intelligence across various scales and dimensions.</li><li>Covered categories like:<ul><li><strong>Mimicry and Imitation</strong>: Reproducing behaviors or sounds.</li><li><strong>Auditory and Visual Creativity</strong>: Expressing oneself using sensory means.</li><li><strong>Communication</strong>: Gauging linguistic capabilities and expressive depth.</li><li><strong>Abstract Thinking</strong>: Handling abstract symbols and concepts.</li><li><strong>Identity and Self-awareness</strong>: Assessing introspection and understanding one's life narrative.</li><li><strong>Problem Solving for Global Challenges</strong>: Evaluating knowledge of global issues and generating solutions.</li><li><strong>Future Planning and Prevention</strong>: Analyzing foresight, planning, and anticipation of challenges.</li><li><strong>Innovation</strong>: Measuring creativity and problem-solving capacities.</li></ul></li></ul></li></ol><p>This dual discussion provided insights into two distinct but vital areas. The first sheds light on the evolution of AI, its challenges, and progress, highlighting the transition from symbolic logic to statistical learning. The second, the MIT, offers a fresh perspective on assessing intelligence, emphasizing the multifaceted nature of cognitive abilities beyond just traditional measures.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 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class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">A summary of the whole conversation.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button 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whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Certainly! Here's a summary of our comprehensive discussion:</p><ol><li><p><strong>Ancient Soundscapes</strong>:</p><ul><li>Explored the possibility that <strong>Neanderthals</strong> utilized <strong>stalactites as lithophones</strong>, creating sounds by striking them.</li><li>Considered the use of <strong>drumheads with objects</strong> like pebbles and arrowheads, which might resonate due to the vibrations of struck stalactites.</li><li>Discussed the concept of <strong>sympathetic resonance</strong> and how the acoustics of caves could amplify sounds.</li><li>Contemplated the <strong>evolution of instruments</strong> from large, static stalactites to portable instruments.</li><li>Delved into the hypothesis of Neanderthals using <strong>swung or spun objects on strings</strong> to produce sound.</li><li>Emphasized the importance of <strong>experimental archaeology</strong> in understanding ancient music practices.</li><li>Highlighted the implications of these sound practices in understanding the cognitive abilities and cultural lives of Neanderthals.</li></ul></li><li><p><strong>Bayesian Framework in Cognitive Science</strong>:</p><ul><li>Described the Bayesian framework's role in understanding cognitive processes.</li><li>Covered topics like <strong>environmental interaction</strong>, feedback and refinement of beliefs, and the evolution of cognitive complexity.</li><li>Discussed how cognitive biases might have evolved and the modern applications of Bayesian insights in AI and personalized medicine.</li></ul></li><li><p><strong>AI's Evolution</strong>:</p><ul><li>Recapped the history of early AI, starting with its focus on the <strong>"propositional picture" of semantic knowledge</strong>.</li><li>Traced the evolution from symbolic AI to the rise of Large Language Models (LLMs).</li><li>Discussed challenges faced by early AI in handling language ambiguities and the transition from symbolic logic to neural networks.</li><li>Covered the ambitious projects like <strong>Doug Lenat's "Cyc"</strong> and <strong>Terry Winograd's work</strong>.</li><li>Addressed the <strong>Winograd Schema Challenge</strong> and the implications of LLMs on rethinking initial AI assumptions.</li></ul></li><li><p><strong>Multiscale Intelligence Test (MIT)</strong>:</p><ul><li>Introduced the MIT as a broad framework for assessing intelligence.</li><li>Discussed various categories, including mimicry, auditory creativity, abstract thinking, problem-solving, and innovation, among others.</li></ul></li></ol><p>Our conversation navigated through the ancient soundscapes of our ancestors, the Bayesian framework's influence on cognitive science, the intricate journey of AI, and the comprehensive approach to intelligence testing. Each topic enriched our understanding of human cognition, the development of artificial intelligence, and the intricate interplay between the past, present, and future of cognitive evolution.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 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class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-50" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">A shorter, narrative style summary.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-51" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto 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8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Certainly!</p><p>In the echoing chambers of ancient caves, we imagined Neanderthals evoking melodies from stalactites and resonating drumheads, revealing the profound role sound played in their lives. These ancient soundscapes became a portal to delve deeper into cognition. Through the lens of the Bayesian framework, we explored the intricate dance of belief formation and refinement, uncovering patterns that weave through human evolution.</p><p>Shifting gears, we journeyed through the evolving landscape of AI—from its nascent days, where logic reigned supreme, to the contemporary era of sophisticated language models. We navigated the labyrinth of challenges that early AI pioneers faced, from grappling with linguistic ambiguities to the ambitious dreams of projects like "Cyc."</p><p>Finally, as if peering into a cognitive kaleidoscope, we delved into the Multiscale Intelligence Test—a panoramic vista that stretches the boundaries of what we understand as intelligence, encompassing mimicry, creativity, problem-solving, and more.</p><p>Together, our discourse danced across ancient rhythms, cognitive landscapes, AI's evolution, and the multifaceted nature of intelligence, painting a rich tapestry of understanding.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 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2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="group w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 gizmo:bg-transparent dark:bg-gray-800 gizmo:dark:bg-transparent" data-testid="conversation-turn-52" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative flex"><img alt="User" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="rounded-sm" src="https://chat.openai.com/_next/image?url=https%3A%2F%2Fs.gravatar.com%2Favatar%2F6241bfe48785687ad5d68f5c836fbe6d%3Fs%3D480%26r%3Dpg%26d%3Dhttps%253A%252F%252Fcdn.auth0.com%252Favatars%252Fna.png&w=96&q=75" style="color: transparent;"></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] gizmo:text-gizmo-gray-600 gizmo:dark:text-gray-300"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="">Connections between the topics.</div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"></path><path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"></path></svg></button></div></div></div></div></div></div></div><div class="group final-completion w-full text-token-text-primary border-b border-black/10 gizmo:border-0 dark:border-gray-900/50 gizmo:dark:border-0 bg-gray-50 gizmo:bg-transparent dark:bg-[#444654] gizmo:dark:bg-transparent" data-testid="conversation-turn-53" style="--avatar-color: #AB68FF;"><div class="p-4 justify-center text-base md:gap-6 md:py-6 m-auto"><div class="flex flex-1 gap-4 text-base mx-auto md:gap-6 gizmo:gap-3 gizmo:md:px-5 gizmo:lg:px-1 gizmo:xl:px-5 md:max-w-2xl lg:max-w-[38rem] gizmo:md:max-w-3xl gizmo:lg:max-w-[40rem] gizmo:xl:max-w-[48rem] xl:max-w-3xl }"><div class="flex-shrink-0 flex flex-col relative items-end"><div><div class="relative p-1 rounded-sm h-9 w-9 text-white flex items-center justify-center" style="background-color: rgb(171, 104, 255); width: 36px; height: 36px;"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon-md" role="img"><text x="-9999" y="-9999">ChatGPT</text><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 23.7219 1.94125 22.4257 1.36341C21.1295 0.785575 19.7249 0.491269 18.3058 0.500197C16.1708 0.495044 14.0893 1.16803 12.3614 2.42214C10.6335 3.67624 9.34853 5.44666 8.6917 7.47815C7.30085 7.76286 5.98686 8.3414 4.8377 9.17505C3.68854 10.0087 2.73073 11.0782 2.02839 12.312C0.956464 14.1591 0.498905 16.2988 0.721698 18.4228C0.944492 20.5467 1.83612 22.5449 3.268 24.1293C2.81966 25.4759 2.66413 26.9026 2.81182 28.3141C2.95951 29.7256 3.40701 31.0892 4.12437 32.3138C5.18791 34.1659 6.8123 35.6322 8.76321 36.5013C10.7141 37.3704 12.8907 37.5973 14.9789 37.1492C15.9208 38.2107 17.0786 39.0587 18.3747 39.6366C19.6709 40.2144 21.0755 40.5087 22.4946 40.4998C24.6307 40.5054 26.7133 39.8321 28.4418 38.5772C30.1704 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20.9586 32.5474 20.7328 32.4332 20.5338C32.319 20.3348 32.154 20.1698 31.955 20.0556ZM35.3055 15.0128C35.2464 14.9765 35.1431 14.9142 35.069 14.8717L27.1045 10.2712C26.906 10.1554 26.6803 10.0943 26.4504 10.0943C26.2206 10.0943 25.9948 10.1554 25.7963 10.2712L16.0726 15.8858V11.9982C16.0715 11.9783 16.0753 11.9585 16.0837 11.9405C16.0921 11.9225 16.1048 11.9068 16.1207 11.8949L24.1719 7.25025C25.4053 6.53903 26.8158 6.19376 28.2383 6.25482C29.6608 6.31589 31.0364 6.78077 32.2044 7.59508C33.3723 8.40939 34.2842 9.53945 34.8334 10.8531C35.3826 12.1667 35.5464 13.6095 35.3055 15.0128ZM14.2424 21.9419L10.8752 19.9981C10.8576 19.9893 10.8423 19.9763 10.8309 19.9602C10.8195 19.9441 10.8122 19.9254 10.8098 19.9058V10.6071C10.8107 9.18295 11.2173 7.78848 11.9819 6.58696C12.7466 5.38544 13.8377 4.42659 15.1275 3.82264C16.4173 3.21869 17.8524 2.99464 19.2649 3.1767C20.6775 3.35876 22.0089 3.93941 23.1034 4.85067C23.0427 4.88379 22.937 4.94215 22.8668 4.98473L14.9024 9.58517C14.7025 9.69878 14.5366 9.86356 14.4215 10.0626C14.3065 10.2616 14.2466 10.4877 14.2479 10.7175L14.2424 21.9419ZM16.071 17.9991L20.4018 15.4978L24.7325 17.9975V22.9985L20.4018 25.4983L16.071 22.9985V17.9991Z" fill="currentColor"></path></svg></div></div></div><div class="relative flex w-[calc(100%-50px)] flex-col gizmo:w-full lg:w-[calc(100%-115px)] agent-turn"><div class="flex-col gap-1 md:gap-3"><div class="flex flex-grow flex-col gap-3 max-w-full"><div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"><div class="markdown prose w-full break-words dark:prose-invert dark"><p>Drawing connections between ancient soundscapes, cognitive frameworks, AI evolution, and the multifaceted nature of intelligence paints a holistic picture of human curiosity and our desire to understand the world:</p><ol><li><p><strong>Echoes of the Past and Cognition</strong>:</p><ul><li>The exploration of Neanderthal soundscapes provides insights into early cognitive abilities. The manipulation and appreciation of sound imply abstract thinking, creativity, and problem-solving, foundational elements of intelligence.</li><li>The Bayesian framework's iterative process of hypothesis and refinement mirrors the way our ancestors might have approached learning—experimenting with sounds, observing results, and refining techniques.</li></ul></li><li><p><strong>Cognitive Evolution and AI</strong>:</p><ul><li>Early AI's attempts to understand language and semantics resonate with our discussions about ancient humans trying to make sense of their environment. Both involve forming hypotheses, testing them, and refining understanding.</li><li>The challenges AI faced in language processing—like ambiguity—echo the challenges ancient cultures might have faced in deciphering meaning from sounds or gestures.</li></ul></li><li><p><strong>Multiscale Intelligence and Soundscapes</strong>:</p><ul><li>The MIT evaluates various dimensions of intelligence, such as mimicry, auditory creativity, and abstract thinking. These facets can be seen in our ancient ancestors' possible practices—mimicking animal sounds, creating melodies, or conceptualizing rhythmic patterns.</li><li>Just as we're exploring AI's capabilities in abstract thinking and communication, our ancient ancestors were pushing the boundaries of their cognitive abilities through their engagement with sound.</li></ul></li><li><p><strong>AI as a Reflection of Human Curiosity</strong>:</p><ul><li>Our journey in AI, from symbolic logic to large language models, mirrors humanity's journey in understanding and representing the world—from mimicking sounds in nature to developing sophisticated music and communication systems.</li><li>The MIT's goal to capture a spectrum of human cognitive abilities is a contemporary echo of our fascination with the cognitive capacities of our ancient ancestors.</li></ul></li></ol><p>In essence, the threads of ancient sound practices, cognitive evolution, the development of AI, and our multifaceted understanding of intelligence intertwine, revealing a narrative of humanity's relentless pursuit of knowledge and understanding.</p></div></div></div><div class="flex justify-between empty:hidden gizmo:justify-start gizmo:gap-3 lg:block"><div class="text-gray-400 flex self-end lg:self-center justify-center gizmo:lg:justify-start mt-2 gizmo:mt-0 visible lg:gap-1 lg:absolute lg:top-0 lg:translate-x-full lg:right-0 lg:mt-0 lg:pl-2 gap-2 md:gap-3"><button class="flex ml-auto gizmo:ml-0 gap-2 items-center rounded-md p-1 text-xs gizmo:gap-1.5 gizmo:pl-0 dark:text-gray-400 dark:hover:bg-gray-700 dark:hover:text-gray-200 disabled:dark:hover:text-gray-400 hover:bg-gray-100 hover:text-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2"></path><rect x="8" y="2" width="8" height="4" rx="1" ry="1"></rect></svg></button><div class="flex gap-1 gizmo:gap-3"><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M14 9V5a3 3 0 0 0-3-3l-4 9v11h11.28a2 2 0 0 0 2-1.7l1.38-9a2 2 0 0 0-2-2.3zM7 22H4a2 2 0 0 1-2-2v-7a2 2 0 0 1 2-2h3"></path></svg></button><button class="p-1 gizmo:pl-0 rounded-md disabled:dark:hover:text-gray-400 dark:hover:text-gray-200 dark:text-gray-400 hover:bg-gray-100 hover:text-gray-700 dark:hover:bg-gray-700"><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" class="icon-sm" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M10 15v4a3 3 0 0 0 3 3l4-9V2H5.72a2 2 0 0 0-2 1.7l-1.38 9a2 2 0 0 0 2 2.3zm7-13h2.67A2.31 2.31 0 0 1 22 4v7a2.31 2.31 0 0 1-2.33 2H17"></path></svg></button></div></div></div></div></div></div></div></div><div class="h-36 md:h-48 flex-shrink-0"></div></div></div></div></div><div class="w-full pt-2 md:pt-0 border-t md:border-t-0 dark:border-white/20 md:border-transparent md:dark:border-transparent md:pl-2 md:w-[calc(100%-.5rem)] absolute bottom-0 left-0 md:bg-vert-light-gradient bg-white dark:bg-gray-800 md:!bg-transparent dark:md:bg-vert-dark-gradient"><form class="stretch mx-2 flex flex-row gap-3 last:mb-2 md:mx-4 md:last:mb-6 lg:mx-auto lg:max-w-2xl xl:max-w-3xl"><div class="relative flex h-full flex-1 items-stretch md:flex-col"><div class="flex w-full items-center"><div class="flex flex-col w-full flex-grow relative border border-black/10 gizmo:border-black/20 gizmo:dark:border-white/30 dark:border-gray-900/50 dark:text-white rounded-xl gizmo:rounded-2xl shadow-xs dark:shadow-xs dark:bg-gray-700 bg-white gizmo:dark:bg-gray-800 gizmo:shadow-[0_0_0_2px_rgba(255,255,255,0.95)] gizmo:dark:shadow-[0_0_0_2px_rgba(52,53,65,0.95)]"><textarea id="prompt-textarea" tabindex="0" data-id="9faec732-1f22-4481-9dc4-d39be901c9cc" rows="1" placeholder="Send a message" class="m-0 w-full resize-none border-0 bg-transparent py-[10px] pr-10 focus:ring-0 focus-visible:ring-0 dark:bg-transparent md:py-4 md:pr-12 gizmo:md:py-3.5 gizmo:placeholder-black/50 gizmo:dark:placeholder-white/50 pl-12 md:pl-[46px]" style="max-height: 200px; 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[multiple]:focus, [type="date"]:focus, [type="datetime-local"]:focus, [type="email"]:focus, [type="month"]:focus, [type="number"]:focus, [type="password"]:focus, [type="search"]:focus, [type="tel"]:focus, [type="text"]:focus, [type="time"]:focus, [type="url"]:focus, [type="week"]:focus, select:focus, textarea:focus { --tw-ring-inset: var(--tw-empty,/*!*/ /*!*/); --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: #2563eb; --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(1px + var(--tw-ring-offset-width)) var(--tw-ring-color); border-color: rgb(37, 99, 235); box-shadow: var(--tw-ring-offset-shadow),var(--tw-ring-shadow),var(--tw-shadow); outline: transparent solid 2px; outline-offset: 2px; }
input::-webkit-input-placeholder, textarea::-webkit-input-placeholder { color: rgb(142, 142, 160); opacity: 1; }
input::placeholder, textarea::placeholder { color: rgb(142, 142, 160); opacity: 1; }
::-webkit-datetime-edit-fields-wrapper { padding: 0px; }
::-webkit-date-and-time-value { min-height: 1.5em; }
::-webkit-datetime-edit, ::-webkit-datetime-edit-day-field, ::-webkit-datetime-edit-hour-field, ::-webkit-datetime-edit-meridiem-field, ::-webkit-datetime-edit-millisecond-field, ::-webkit-datetime-edit-minute-field, ::-webkit-datetime-edit-month-field, ::-webkit-datetime-edit-second-field, ::-webkit-datetime-edit-year-field { padding-bottom: 0px; padding-top: 0px; }
select { background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' viewBox='0 0 20 20'%3E%3Cpath stroke='%238e8ea0' stroke-linecap='round' stroke-linejoin='round' stroke-width='1.5' d='m6 8 4 4 4-4'/%3E%3C/svg%3E"); background-position: right 0.5rem center; background-repeat: no-repeat; background-size: 1.5em 1.5em; padding-right: 2.5rem; -webkit-print-color-adjust: exact; }
[multiple] { background-image: none; background-position: 0px 0px; background-repeat: repeat; background-size: initial; padding-right: 0.75rem; -webkit-print-color-adjust: inherit; }
[type="checkbox"], [type="radio"] { --tw-shadow: 0 0 transparent; appearance: none; background-color: rgb(255, 255, 255); background-origin: border-box; border-color: rgb(142, 142, 160); border-width: 1px; color: rgb(37, 99, 235); display: inline-block; flex-shrink: 0; height: 1rem; padding: 0px; -webkit-print-color-adjust: exact; user-select: none; vertical-align: middle; width: 1rem; }
[type="checkbox"] { border-radius: 0px; }
[type="radio"] { border-radius: 100%; }
[type="checkbox"]:focus, [type="radio"]:focus { --tw-ring-inset: var(--tw-empty,/*!*/ /*!*/); --tw-ring-offset-width: 2px; --tw-ring-offset-color: #fff; --tw-ring-color: #2563eb; --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(2px + var(--tw-ring-offset-width)) var(--tw-ring-color); box-shadow: var(--tw-ring-offset-shadow),var(--tw-ring-shadow),var(--tw-shadow); outline: transparent solid 2px; outline-offset: 2px; }
[type="checkbox"]:checked, [type="radio"]:checked { background-color: currentcolor; background-position: 50% center; background-repeat: no-repeat; background-size: 100% 100%; border-color: transparent; }
[type="checkbox"]:checked { background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg viewBox='0 0 16 16' fill='%23fff' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M12.207 4.793a1 1 0 0 1 0 1.414l-5 5a1 1 0 0 1-1.414 0l-2-2a1 1 0 0 1 1.414-1.414L6.5 9.086l4.293-4.293a1 1 0 0 1 1.414 0z'/%3E%3C/svg%3E"); }
[type="radio"]:checked { background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg viewBox='0 0 16 16' fill='%23fff' xmlns='http://www.w3.org/2000/svg'%3E%3Ccircle cx='8' cy='8' r='3'/%3E%3C/svg%3E"); }
[type="checkbox"]:checked:focus, [type="checkbox"]:checked:hover, [type="radio"]:checked:focus, [type="radio"]:checked:hover { background-color: currentcolor; border-color: transparent; }
[type="checkbox"]:indeterminate { background-color: currentcolor; background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' viewBox='0 0 16 16'%3E%3Cpath stroke='%23fff' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='M4 8h8'/%3E%3C/svg%3E"); background-position: 50% center; background-repeat: no-repeat; background-size: 100% 100%; border-color: transparent; }
[type="checkbox"]:indeterminate:focus, [type="checkbox"]:indeterminate:hover { background-color: currentcolor; border-color: transparent; }
[type="file"] { background: initial; border-color: inherit; border-radius: 0px; border-width: 0px; font-size: inherit; line-height: inherit; padding: 0px; }
[type="file"]:focus { outline: -webkit-focus-ring-color auto 1px; }
h1 { font-size: 1.875rem; line-height: 2.25rem; }
h1, h2, h3 { font-weight: 600; }
h2, h3 { font-size: 1.5rem; line-height: 2rem; }
*, ::after, ::before { --tw-border-spacing-x: 0; --tw-border-spacing-y: 0; --tw-translate-x: 0; --tw-translate-y: 0; --tw-rotate: 0; --tw-skew-x: 0; --tw-skew-y: 0; --tw-scale-x: 1; --tw-scale-y: 1; --tw-pan-x: ; --tw-pan-y: ; --tw-pinch-zoom: ; --tw-scroll-snap-strictness: proximity; --tw-gradient-from-position: ; --tw-gradient-via-position: ; --tw-gradient-to-position: ; --tw-ordinal: ; --tw-slashed-zero: ; --tw-numeric-figure: ; --tw-numeric-spacing: ; --tw-numeric-fraction: ; --tw-ring-inset: ; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgba(69,89,164,.5); --tw-ring-offset-shadow: 0 0 transparent; --tw-ring-shadow: 0 0 transparent; --tw-shadow: 0 0 transparent; --tw-shadow-colored: 0 0 transparent; --tw-blur: ; --tw-brightness: ; --tw-contrast: ; --tw-grayscale: ; --tw-hue-rotate: ; --tw-invert: ; --tw-saturate: ; --tw-sepia: ; --tw-drop-shadow: ; --tw-backdrop-blur: ; --tw-backdrop-brightness: ; --tw-backdrop-contrast: ; --tw-backdrop-grayscale: ; --tw-backdrop-hue-rotate: ; --tw-backdrop-invert: ; --tw-backdrop-opacity: ; --tw-backdrop-saturate: ; --tw-backdrop-sepia: ; }
::-webkit-backdrop { --tw-border-spacing-x: 0; --tw-border-spacing-y: 0; --tw-translate-x: 0; --tw-translate-y: 0; --tw-rotate: 0; --tw-skew-x: 0; --tw-skew-y: 0; --tw-scale-x: 1; --tw-scale-y: 1; --tw-pan-x: ; --tw-pan-y: ; --tw-pinch-zoom: ; --tw-scroll-snap-strictness: proximity; --tw-gradient-from-position: ; --tw-gradient-via-position: ; --tw-gradient-to-position: ; --tw-ordinal: ; --tw-slashed-zero: ; --tw-numeric-figure: ; --tw-numeric-spacing: ; --tw-numeric-fraction: ; --tw-ring-inset: ; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgba(69,89,164,.5); --tw-ring-offset-shadow: 0 0 transparent; --tw-ring-shadow: 0 0 transparent; --tw-shadow: 0 0 transparent; --tw-shadow-colored: 0 0 transparent; --tw-blur: ; --tw-brightness: ; --tw-contrast: ; --tw-grayscale: ; --tw-hue-rotate: ; --tw-invert: ; --tw-saturate: ; --tw-sepia: ; --tw-drop-shadow: ; --tw-backdrop-blur: ; --tw-backdrop-brightness: ; --tw-backdrop-contrast: ; --tw-backdrop-grayscale: ; --tw-backdrop-hue-rotate: ; --tw-backdrop-invert: ; --tw-backdrop-opacity: ; --tw-backdrop-saturate: ; --tw-backdrop-sepia: ; }
::backdrop { --tw-border-spacing-x: 0; --tw-border-spacing-y: 0; --tw-translate-x: 0; --tw-translate-y: 0; --tw-rotate: 0; --tw-skew-x: 0; --tw-skew-y: 0; --tw-scale-x: 1; --tw-scale-y: 1; --tw-pan-x: ; --tw-pan-y: ; --tw-pinch-zoom: ; --tw-scroll-snap-strictness: proximity; --tw-gradient-from-position: ; --tw-gradient-via-position: ; --tw-gradient-to-position: ; --tw-ordinal: ; --tw-slashed-zero: ; --tw-numeric-figure: ; --tw-numeric-spacing: ; --tw-numeric-fraction: ; --tw-ring-inset: ; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgba(69,89,164,.5); --tw-ring-offset-shadow: 0 0 transparent; --tw-ring-shadow: 0 0 transparent; --tw-shadow: 0 0 transparent; --tw-shadow-colored: 0 0 transparent; --tw-blur: ; --tw-brightness: ; --tw-contrast: ; --tw-grayscale: ; --tw-hue-rotate: ; --tw-invert: ; --tw-saturate: ; --tw-sepia: ; --tw-drop-shadow: ; --tw-backdrop-blur: ; --tw-backdrop-brightness: ; --tw-backdrop-contrast: ; --tw-backdrop-grayscale: ; --tw-backdrop-hue-rotate: ; --tw-backdrop-invert: ; --tw-backdrop-opacity: ; --tw-backdrop-saturate: ; --tw-backdrop-sepia: ; }
:root { --white: #fff; --black: #000; --gray-50: #f7f7f8; --gray-100: #ececf1; --gray-200: #d9d9e3; --gray-300: #c5c5d2; --gray-400: #acacbe; --gray-500: #8e8ea0; --gray-600: #565869; --gray-700: #40414f; --gray-800: #343541; --gray-900: #202123; --gray-950: #050509; --gizmo-gray-500: #999; --gizmo-gray-600: #666; --gizmo-gray-950: #0f0f0f; }
html { --text-primary: var(--gray-800); --text-secondary: var(--gray-600); --text-tertiary: var(--gray-500); --surface-primary: var(--white); --surface-secondary: var(--gray-50); --surface-tertiary: var(--gray-100); --border-light: var(--gray-100); --border-medium: var(--gray-200); --border-heavy: var(--gray-300); }
.dark { --text-primary: var(--gray-100); --text-secondary: var(--gray-300); --text-tertiary: var(--gray-500); --surface-primary: var(--gray-900); --surface-secondary: var(--gray-800); --surface-tertiary: var(--gray-700); --border-light: var(--gray-700); --border-medium: var(--gray-600); --border-heavy: var(--gray-500); }
.gizmo { --text-primary: var(--gray-800); --text-secondary: var(--gizmo-gray-600); --text-tertiary: var(--gizmo-gray-500); --surface-primary: var(--white); --surface-secondary: var(--gray-50); --surface-tertiary: var(--gray-100); --border-light: rgba(0,0,0,.1); --border-medium: rgba(0,0,0,.15); --border-heavy: rgba(0,0,0,.2); }
.gizmo.dark { --text-primary: var(--gray-100); --text-secondary: var(--gray-300); --text-tertiary: var(--gizmo-gray-500); --surface-primary: var(--gray-900); --surface-secondary: var(--gray-800); --surface-tertiary: var(--gray-700); --border-light: rgba(217,217,227,.1); --border-medium: rgba(217,217,227,.15); --border-heavy: rgba(217,217,227,.2); }
textarea:focus { border-color: inherit; box-shadow: none; outline: none; }
::-webkit-scrollbar { height: 1rem; width: 0.5rem; }
::-webkit-scrollbar:horizontal { height: 0.5rem; width: 1rem; }
::-webkit-scrollbar-track { background-color: transparent; border-radius: 9999px; }
::-webkit-scrollbar-thumb { --tw-border-opacity: 1; background-color: rgba(217, 217, 227, 0.8); border-color: rgba(255,255,255,var(--tw-border-opacity)); border-radius: 9999px; border-width: 1px; }
::-webkit-scrollbar-thumb:hover { --tw-bg-opacity: 1; background-color: rgba(236,236,241,var(--tw-bg-opacity)); }
.dark::-webkit-scrollbar-thumb { --tw-bg-opacity: 1; background-color: rgba(86,88,105,var(--tw-bg-opacity)); }
.dark::-webkit-scrollbar-thumb:hover { --tw-bg-opacity: 1; background-color: rgba(172,172,190,var(--tw-bg-opacity)); }
@media (min-width: 768px) {
.scrollbar-trigger ::-webkit-scrollbar-thumb { visibility: hidden; }
.scrollbar-trigger:hover ::-webkit-scrollbar-thumb { visibility: visible; }
}
.container { width: 100%; }
@media (min-width: 640px) {
.container { max-width: 640px; }
}
@media (min-width: 768px) {
.container { max-width: 768px; }
}
@media (min-width: 1024px) {
.container { max-width: 1024px; }
}
@media (min-width: 1280px) {
.container { max-width: 1280px; }
}
@media (min-width: 1536px) {
.container { max-width: 1536px; }
}
.prose { color: var(--tw-prose-body); max-width: 65ch; }
.prose :where([class~="lead"]):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-lead); font-size: 1.25em; line-height: 1.6; margin-bottom: 1.2em; margin-top: 1.2em; }
.prose :where(a):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-links); font-weight: 500; text-decoration: underline; }
.prose :where(strong):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-bold); font-weight: 600; }
.prose :where(a strong):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(blockquote strong):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(thead th strong):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(ol):not(:where([class~="not-prose"] *)) { list-style-type: decimal; margin-bottom: 1.25em; margin-top: 1.25em; padding-left: 1.625em; }
.prose :where(ol[type="A"]):not(:where([class~="not-prose"] *)) { list-style-type: upper-alpha; }
.prose :where(ol[type="a"]):not(:where([class~="not-prose"] *)) { list-style-type: lower-alpha; }
.prose :where():not(:where([class~="not-prose"] *)) { list-style-type: upper-alpha; }
.prose :where():not(:where([class~="not-prose"] *)) { list-style-type: lower-alpha; }
.prose :where(ol[type="I"]):not(:where([class~="not-prose"] *)) { list-style-type: upper-roman; }
.prose :where(ol[type="i"]):not(:where([class~="not-prose"] *)) { list-style-type: lower-roman; }
.prose :where():not(:where([class~="not-prose"] *)) { list-style-type: upper-roman; }
.prose :where():not(:where([class~="not-prose"] *)) { list-style-type: lower-roman; }
.prose :where(ol[type="1"]):not(:where([class~="not-prose"] *)) { list-style-type: decimal; }
.prose :where(ul):not(:where([class~="not-prose"] *)) { list-style-type: disc; margin-bottom: 1.25em; margin-top: 1.25em; padding-left: 1.625em; }
.prose :where(ol > li):not(:where([class~="not-prose"] *))::marker { color: var(--tw-prose-counters); font-weight: 400; }
.prose :where(ul > li):not(:where([class~="not-prose"] *))::marker { color: var(--tw-prose-bullets); }
.prose :where(hr):not(:where([class~="not-prose"] *)) { border-color: var(--tw-prose-hr); border-top-width: 1px; margin-bottom: 3em; margin-top: 3em; }
.prose :where(blockquote):not(:where([class~="not-prose"] *)) { border-left-color: var(--tw-prose-quote-borders); border-left-width: 0.25rem; color: var(--tw-prose-quotes); font-style: normal; font-weight: 500; margin-bottom: 1.6em; margin-top: 1.6em; padding-left: 1em; quotes: "“" "”" "‘" "’"; }
.prose :where(blockquote p:first-of-type):not(:where([class~="not-prose"] *))::before { content: open-quote; }
.prose :where(blockquote p:last-of-type):not(:where([class~="not-prose"] *))::after { content: close-quote; }
.prose :where(h1):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-headings); font-size: 2.25em; font-weight: 800; line-height: 1.11111; margin-bottom: 0.888889em; margin-top: 0px; }
.prose :where(h1 strong):not(:where([class~="not-prose"] *)) { color: inherit; font-weight: 900; }
.prose :where(h2):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-headings); font-size: 1.5em; font-weight: 700; line-height: 1.33333; margin-bottom: 1em; margin-top: 2em; }
.prose :where(h2 strong):not(:where([class~="not-prose"] *)) { color: inherit; font-weight: 800; }
.prose :where(h3):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-headings); font-size: 1.25em; font-weight: 600; line-height: 1.6; margin-bottom: 0.6em; margin-top: 1.6em; }
.prose :where(h3 strong):not(:where([class~="not-prose"] *)) { color: inherit; font-weight: 700; }
.prose :where(h4):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-headings); font-weight: 600; line-height: 1.5; margin-bottom: 0.5em; margin-top: 1.5em; }
.prose :where(h4 strong):not(:where([class~="not-prose"] *)) { color: inherit; font-weight: 700; }
.prose :where(img):not(:where([class~="not-prose"] *)) { margin-bottom: 2em; margin-top: 2em; }
.prose :where(figure > *):not(:where([class~="not-prose"] *)) { margin-bottom: 0px; margin-top: 0px; }
.prose :where(figcaption):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-captions); font-size: 0.875em; line-height: 1.42857; margin-top: 0.857143em; }
.prose :where(code):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-code); font-size: 0.875em; font-weight: 600; }
.prose :where(code):not(:where([class~="not-prose"] *))::before { content: "`"; }
.prose :where(code):not(:where([class~="not-prose"] *))::after { content: "`"; }
.prose :where(a code):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(h1 code):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(h2 code):not(:where([class~="not-prose"] *)) { color: inherit; font-size: 0.875em; }
.prose :where(h3 code):not(:where([class~="not-prose"] *)) { color: inherit; font-size: 0.9em; }
.prose :where(h4 code):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(blockquote code):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(thead th code):not(:where([class~="not-prose"] *)) { color: inherit; }
.prose :where(pre):not(:where([class~="not-prose"] *)) { background-color: transparent; border-radius: 0.375rem; color: currentcolor; font-size: 0.875em; font-weight: 400; line-height: 1.71429; margin: 0px; overflow-x: auto; padding: 0px; }
.prose :where(pre code):not(:where([class~="not-prose"] *)) { background-color: transparent; border-radius: 0px; border-width: 0px; color: inherit; font-family: inherit; font-size: inherit; font-weight: inherit; line-height: inherit; padding: 0px; }
.prose :where(pre code):not(:where([class~="not-prose"] *))::before { content: none; }
.prose :where(pre code):not(:where([class~="not-prose"] *))::after { content: none; }
.prose :where(table):not(:where([class~="not-prose"] *)) { font-size: 0.875em; line-height: 1.71429; margin-bottom: 2em; margin-top: 2em; table-layout: auto; text-align: left; width: 100%; }
.prose :where(thead):not(:where([class~="not-prose"] *)) { border-bottom-color: var(--tw-prose-th-borders); border-bottom-width: 1px; }
.prose :where(thead th):not(:where([class~="not-prose"] *)) { color: var(--tw-prose-headings); font-weight: 600; padding-bottom: 0.571429em; padding-left: 0.571429em; padding-right: 0.571429em; vertical-align: bottom; }
.prose :where(tbody tr):not(:where([class~="not-prose"] *)) { border-bottom-color: var(--tw-prose-td-borders); border-bottom-width: 1px; }
.prose :where(tbody tr:last-child):not(:where([class~="not-prose"] *)) { border-bottom-width: 0px; }
.prose :where(tbody td):not(:where([class~="not-prose"] *)) { vertical-align: baseline; }
.prose :where(tfoot):not(:where([class~="not-prose"] *)) { border-top-color: var(--tw-prose-th-borders); border-top-width: 1px; }
.prose :where(tfoot td):not(:where([class~="not-prose"] *)) { vertical-align: top; }
.prose { --tw-prose-body: #374151; --tw-prose-headings: #111827; --tw-prose-lead: #4b5563; --tw-prose-links: #111827; --tw-prose-bold: #111827; --tw-prose-counters: #6b7280; --tw-prose-bullets: #d1d5db; --tw-prose-hr: #e5e7eb; --tw-prose-quotes: #111827; --tw-prose-quote-borders: #e5e7eb; --tw-prose-captions: #6b7280; --tw-prose-code: #111827; --tw-prose-pre-code: #e5e7eb; --tw-prose-pre-bg: #1f2937; --tw-prose-th-borders: #d1d5db; --tw-prose-td-borders: #e5e7eb; --tw-prose-invert-body: #d1d5db; --tw-prose-invert-headings: #fff; --tw-prose-invert-lead: #9ca3af; --tw-prose-invert-links: #fff; --tw-prose-invert-bold: #fff; --tw-prose-invert-counters: #9ca3af; --tw-prose-invert-bullets: #4b5563; --tw-prose-invert-hr: #374151; --tw-prose-invert-quotes: #f3f4f6; --tw-prose-invert-quote-borders: #374151; --tw-prose-invert-captions: #9ca3af; --tw-prose-invert-code: #fff; --tw-prose-invert-pre-code: #d1d5db; --tw-prose-invert-pre-bg: rgba(0,0,0,.5); --tw-prose-invert-th-borders: #4b5563; --tw-prose-invert-td-borders: #374151; font-size: 1rem; line-height: 1.75; }
.prose :where(p):not(:where([class~="not-prose"] *)) { margin-bottom: 1.25em; margin-top: 1.25em; }
.prose :where(video):not(:where([class~="not-prose"] *)) { margin-bottom: 2em; margin-top: 2em; }
.prose :where(figure):not(:where([class~="not-prose"] *)) { margin-bottom: 2em; margin-top: 2em; }
.prose :where(li):not(:where([class~="not-prose"] *)) { margin-bottom: 0.5em; margin-top: 0.5em; }
.prose :where(ol > li):not(:where([class~="not-prose"] *)) { padding-left: 0.375em; }
.prose :where(ul > li):not(:where([class~="not-prose"] *)) { padding-left: 0.375em; }
.prose :where(.prose > ul > li p):not(:where([class~="not-prose"] *)) { margin-bottom: 0.75em; margin-top: 0.75em; }
.prose :where(.prose > ul > li > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 1.25em; }
.prose :where(.prose > ul > li > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 1.25em; }
.prose :where(.prose > ol > li > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 1.25em; }
.prose :where(.prose > ol > li > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 1.25em; }
.prose :where(ul ul, ul ol, ol ul, ol ol):not(:where([class~="not-prose"] *)) { margin-bottom: 0.75em; margin-top: 0.75em; }
.prose :where(hr + *):not(:where([class~="not-prose"] *)) { margin-top: 0px; }
.prose :where(h2 + *):not(:where([class~="not-prose"] *)) { margin-top: 0px; }
.prose :where(h3 + *):not(:where([class~="not-prose"] *)) { margin-top: 0px; }
.prose :where(h4 + *):not(:where([class~="not-prose"] *)) { margin-top: 0px; }
.prose :where(thead th:first-child):not(:where([class~="not-prose"] *)) { padding-left: 0px; }
.prose :where(thead th:last-child):not(:where([class~="not-prose"] *)) { padding-right: 0px; }
.prose :where(tbody td, tfoot td):not(:where([class~="not-prose"] *)) { padding: 0.571429em; }
.prose :where(tbody td:first-child, tfoot td:first-child):not(:where([class~="not-prose"] *)) { padding-left: 0px; }
.prose :where(tbody td:last-child, tfoot td:last-child):not(:where([class~="not-prose"] *)) { padding-right: 0px; }
.prose :where(.prose > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 0px; }
.prose :where(.prose > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 0px; }
.prose-sm :where(.prose > ul > li p):not(:where([class~="not-prose"] *)) { margin-bottom: 0.571429em; margin-top: 0.571429em; }
.prose-sm :where(.prose > ul > li > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 1.14286em; }
.prose-sm :where(.prose > ul > li > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 1.14286em; }
.prose-sm :where(.prose > ol > li > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 1.14286em; }
.prose-sm :where(.prose > ol > li > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 1.14286em; }
.prose-sm :where(.prose > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 0px; }
.prose-sm :where(.prose > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 0px; }
.prose-base :where(.prose > ul > li p):not(:where([class~="not-prose"] *)) { margin-bottom: 0.75em; margin-top: 0.75em; }
.prose-base :where(.prose > ul > li > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 1.25em; }
.prose-base :where(.prose > ul > li > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 1.25em; }
.prose-base :where(.prose > ol > li > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 1.25em; }
.prose-base :where(.prose > ol > li > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 1.25em; }
.prose-base :where(.prose > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 0px; }
.prose-base :where(.prose > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 0px; }
.prose-lg :where(.prose > ul > li p):not(:where([class~="not-prose"] *)) { margin-bottom: 0.888889em; margin-top: 0.888889em; }
.prose-lg :where(.prose > ul > li > :first-child):not(:where([class~="not-prose"] *)) { margin-top: 1.33333em; }
.prose-lg :where(.prose > ul > li > :last-child):not(:where([class~="not-prose"] *)) { margin-bottom: 1.33333em; }