David is an OG in AI who has been at the forefront of many of the major breakthroughs of the past decade. His resume: VP of Engineering at OpenAI, a key contributor to Google Brain, co-founder of Adept, and now leading Amazon’s SF AGI Lab.
In this episode we focused on how far test-time compute gets us, the real implications of DeepSeek, what agents milestones he’s looking for and more.
0:00 Intro
1:37 DeepSeek Reactions and Market Implications
4:23 Challenges in Building AGI
8:22 Research Problems in AI Development
11:38 The Future of AI Agents
15:36 How to Make a Large Action Model
20:08 The Path to Reliable Agents
24:29 Future Human-Computer Interaction
25:23 Specialized Models and Policy
28:59 Amazon's Role in AGI Development
30:56 Data Labeling and Team Building
37:00 Reflections on OpenAI
42:35 Quickfire
