Practical AI: Machine Learning, Data Science
Technology
What’s the current reality and practical implications of using 3D environments for simulation and synthetic data creation? In this episode, we cut right through the hype of the Metaverse, Multiverse, Omniverse, and all the “verses” to understand how 3D assets and tooling are actually helping AI developers develop industrial robots, autonomous vehicles, and more. Beau Perschall is at the center of these innovations in his work with NVIDIA, and there is no one better to help us explore the topic!
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Show Notes:
Something missing or broken? PRs welcome!
Timestamps:
(00:00) - Welcome to Practical AI
(00:42) - Beau Perschall
(05:30) - Omniverse 101
(10:27) - What can you do in the omniverse?
(13:26) - Will Omniverse be unique for everyone?
(20:13) - Will Omniverse have good 3D?
(26:39) - Omniverse in context
(30:43) - Synthetic data
(35:31) - Nvidia's plan for low internet areas
(38:44) - What keeps you up at night?
(41:11) - Wrap up
(41:46) - Outro
Rise of the AI PC & local LLMs
AI in the U.S. Congress
First impressions of GPT-4o
Full-stack approach for effective AI agents
Autonomous fighter jets?!
Private, open source chat UIs
Mamba & Jamba
Udio & the age of multi-modal AI
RAG continues to rise
Should kids still learn to code?
AI vs software devs
Prompting the future
Generating the future of art & entertainment
YOLOv9: Computer vision is alive and well
Representation Engineering (Activation Hacking)
Leading the charge on AI in National Security
Gemini vs OpenAI
Data synthesis for SOTA LLMs
Large Action Models (LAMs) & Rabbits 🐇
Collaboration & evaluation for LLM apps
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