AI systems are improving fast, but the story is not just about bigger models or better benchmarks. In this episode, Prakash Narayanan and Nathan Labenz explore why model costs are falling even as capabilities rise, and what that means for distillation, release cycles, and recursive self-improvement.
Lewis Hammond joins to examine how multi-agent systems can miscoordinate, compete, or even drift toward tacit collusion, while Wayne Nelms explains why GPU compute is starting to look like a financial market with transaction indices, futures, capacity contracts, and hedging against obsolescence. The closing conversation widens to governance, medicine, self-driving cars, mathematics, and the pressure increasing compute growth places on institutions.
Show Notes
Prakash Narayanan and Nathan Labenz talk with Lewis Hammond and Wayne Nelms about how AI systems are getting cheaper and more capable, while the risks around coordination, cooperation, and tacit collusion are getting harder to ignore. The conversation also covers model distillation, recursive self-improvement, GPU futures, compute hedging, and the financial structure emerging around AI infrastructure.
Chapters
(0:00) Smaller models, bigger gains.
(1:11) When AI agents cooperate against us.
(2:00) GPU compute needs a financial market.
(2:55) Brute-force compute can break standards.
(5:13) Opening and model release race
(7:29) Why models are getting cheaper
(12:24) How AI models are judged
(18:20) Why frontier models converge
(19:54) Distillation and smaller models
(21:12) Recursive self-improvement
(22:17) The collapse in AI prices
(28:48) Why multi-agent AI matters
(35:43) Three multi-agent failure modes
(48:37) How agents learn cooperation
(53:27) Detecting tacit collusion
(1:11:26) A positive vision for AI cooperation
(1:17:00) What Ornn does
(1:18:34) GPU pricing and hedging
(1:22:18) Building a transaction index
(1:24:43) Why compute prices need real transactions
(1:34:13) GPU futures and capacity contracts
(1:53:34) How long GPUs stay useful
(1:53:44) Hedging chip obsolescence risk
(1:53:54) The future of compute markets
(1:59:53) Agentic startups and compute economics
(2:07:37) Brute-force compute and RSA
(2:17:07) AI and self-driving cars
(2:40:03) AI, mathematics, and peer review
(2:40:13) Why AI doctors may win
(2:46:52) Medicine after chatbots
Guests:
Lewis Hammond — Research Director, Cooperative AI Foundation (𝕏 | LinkedIn)
Wayne Nelms — Co-Founder, Ornn (𝕏 | LinkedIn)
