Discussing the Relationship Between Generative AI Course and Transformer Algorithm

A discussion about the first course on generative AI at Berkeley, emphasizing the statistical models utilized rather than the brain structure. The episode highlights popular models like diffusion, GANs, and VAEs taught in the course.

Transcript

chevron_right

Play full episode

chevron_right

Transcript

Episode notes

This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.

If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai

In episode #159 of Eye on AI, Craig Smith sits down with Peter Chen, the co-founder and CEO of Covariant, in a deep dive into the world of AI-driven robotics.

Peter shares his journey from his early days in China to his pivotal role in shaping the future of AI at Covariant. He discusses the philosophies that guided his work at OpenAI and how these have influenced Covariant's mission in robotics.

This episode unveils how Covariant is harnessing AI to build foundational models for robotics, discussing the intersection of reinforcement learning, generative models, and the broader implications for the field. Peter elaborates on the challenges and breakthroughs in developing AI agents that can operate in dynamic, real-world environments, providing insights into the future of robotics and AI integration.

Join us for this insightful conversation, where Peter Chen maps out the evolving landscape of AI in robotics, shedding light on how Covariant is pushing the boundaries of what's possible.

Stay updated:

Craig Smith's Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Preview and Introduction

(03:10) Peter Chen Journey in AI

(09:53) The Evolution of Generative AI and Transformer Models

(12:21) The Concept of World Models in AI

(14:03) Building Robust Role Models in AI

(20:48) Training AI: From Video Analysis to Real-World Interaction

(23:10) The Three Pillars of Building a Robotic Foundation Model

(27:36) Architectural Insights of Covariant's Foundation Model

(33:20) Adapting AI Models to Diverse Hardware