Uber’s self-driving car showed no signs of slowing before fatal crash, police say
The vehicle was traveling at 40 mph
Making sense of the Facebook and Cambridge Analytica nightmare
The firm harvested data from 50 million Facebook profiles, but now what?
This year, over 100,000 developers told us how they learn, build their careers, which tools they’re using, and what they want in a job.
Women must act now, or male-designed robots will take over our lives
Algorithms are displaying white male bias, and automation is decimating our jobs – we have a lot to lose unless we get involved
China wants to shape the global future of artificial intelligence
Drawing up technical standards is an early attempt to control how AI evolves worldwide.
Chinese AI isn't beating the U.S. yet — and may never catch up
China, intent on dominating artificial intelligence in a race with the United States, is said to be on a steep ascent toward at least a tie. But a number of AI experts say that while China can come close, it will be hard to catch up completely.
AI is already learning how to discriminate
What happens when robots take our jobs, or take on military roles, or drive our vehicles? When we ask these questions about the rapidly-expanding role of AI, there are others we’re often overlooking—like the subject of a WEF paper released this week: how do we prevent discrimination and marginalization of humans in artificial intelligence?
Learning to find 'quiet' earthquakes
Researchers create algorithm that can separate small disturbances from seismic noise
Comparing Deep Learning Frameworks: A Rosetta Stone Approach
In contrast, the repo we are releasing as a full version 1.0 today is like a Rosetta Stone for deep learning frameworks, showing the model building process end to end in the different frameworks. All of these types of efforts combined result in a traveller ready to live in an environment with many languages.
A List of Chip/IP for Deep Learning (keep updating)
Machine Learning, especially Deep Learning technology is driving the evolution of artificial intelligence (AI). At the beginning, deep learning has primarily been a software play. Start from the year 2016, the need for more efficient hardware acceleration of AI/ML/DL was recognized in academia and industry. This year, we saw more and more players, including world’s top semiconductor companies as well as a number of startups, even tech giants Google, have jumped into the race. I believe that it could be very interesting to look at them together. So, I build this list of AI/ML/DL ICs and IPs on Github and keep updating. If you have any suggestion or new information, please let me know.