Noam Brown, renowned AI researcher and key figure at OpenAI, joins us for a deep dive into the o1 release. Recorded just one day before o1’s full public debut, this episode explores the groundbreaking advancements and challenges behind this innovative test-time compute model.
We discuss the technical breakthroughs that set o1 apart, its unique capabilities compared to previous models, and how it disrupts traditional paradigms in AI development. Noam also shares insights into OpenAI’s approach to innovation, the economic realities of scaling AI, and what the future holds for the field.
[0:00] Intro
[0:50] Scaling Model Capabilities and Economic Constraints
[2:48] Excitement Around Test Time Compute
[4:50] Challenges and Future Directions in AI Research
[8:11] Noam Brown's Journey and OpenAI's Research Focus
[16:08] The Role of Specialized Models and Tools
[21:18] Unexpected Use Cases and Future Milestones
[23:44] Proof of Concept: o1's Capabilities
[24:48] The Bitter Lesson: Insights from Richard Sutton
[25:59] Scaffolding Techniques and Their Future
[27:56] Challenges in Academia and AI Research
[30:30] Evaluating AI Models: Metrics and Trends
[34:47] The Role of AI in Social Sciences
[39:39] AI Agents and Emergent Communication
[40:17] Future of AI Robotics
[41:13] Advancing Scientific Research with AI
[43:30] Quickfire
With your co-hosts:
@jacobeffron
- Partner at Redpoint, Former PM Flatiron Health
@patrickachase
- Partner at Redpoint, Former ML Engineer LinkedIn
@ericabrescia
- Former COO Github, Founder Bitnami (acq’d by VMWare)
@jordan_segall
- Partner at Redpoint
