Update docs with NVAIE messaging (#6162) (#6167)

Update docs with NVAIE messaging

Co-authored-by: David Zier <42390249+dzier@users.noreply.github.com>

docs/user_guide/faq.md

@@ -170,6 +170,7 @@ delivering an entire end-to-end AI platform. Four key benefits:
 
 ### Enterprise-Grade Support, Security & API Stability:
 
+<<<<<<< HEAD
 Business-critical AI projects stay on track with NVIDIA Enterprise Support,
 available globally to assist both IT teams with deploying and managing the
 lifecycle of AI applications and the developer teams with building AI
@@ -203,3 +204,38 @@ including savings from reduced time and energy consumption.
 Cloud, Data Center, Edge Optimized and certified to ensure reliable performance
 whether it’s running your AI in the public cloud, virtualized data centers, or
 on DGX systems.
+=======
+Business-critical AI projects stay on track with NVIDIA Enterprise Support, 
+available globally to assist both IT teams with deploying and managing the 
+lifecycle of AI applications and the developer teams with building AI 
+applications.  Support includes maintenance updates, dependable SLAs and 
+response times.  Regular security reviews and priority notifications mitigate 
+potential risk of unmanaged opensource and ensure compliance with corporate 
+standards.  Finally, long term support and regression testing ensures API 
+stability between releases.
+
+### Speed time to production with AI Workflows & Pretrained Models: 
+To reduce the complexity of developing common AI applications, NVIDIA AI 
+Enterprise includes 
+[AI workflows](https://www.nvidia.com/en-us/launchpad/ai/workflows/) which are 
+reference applications for specific business outcomes such as Intelligent 
+Virtual Assistants and Digital Fingerprinting for real-time cybersecurity threat 
+detection.  AI workflow reference applications may include 
+[AI frameworks](https://docs.nvidia.com/deeplearning/frameworks/index.html) and 
+[pretrained models](https://developer.nvidia.com/ai-models), 
+[Helm Charts](https://catalog.ngc.nvidia.com/helm-charts), 
+[Jupyter Notebooks](https://developer.nvidia.com/run-jupyter-notebooks) and 
+[documentation](https://docs.nvidia.com/ai-enterprise/index.html#overview).
+
+### Performance for Efficiency and Cost Savings: 
+Using accelerated compute for AI workloads such as data process with 
+[NVIDIA RAPIDS Accelerator](https://developer.nvidia.com/rapids) for Apache 
+Spark and inference with Triton Inference Sever delivers better performance 
+which also improves efficiency and reduces operation and infrastructure costs, 
+including savings from reduced time and energy consumption.
+
+### Optimized and Certified to Deploy Everywhere: 
+Cloud, Data Center, Edge Optimized and certified to ensure reliable performance 
+whether it’s running your AI in the public cloud, virtualized data centers, or 
+on DGX systems. 
+>>>>>>> bb880ba3 (Update docs with NVAIE messaging (#6162) (#6167))