Build Buffers, Not Precise Plans

Zvi Mowshowitz advises Nathan Labenz to keep large financial buffers, avoid false precision, and plan around scenarios rather than fragile optimization.

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Episode notes

Zvi Mowshowitz returns to survey the current AI landscape, from recursive self-improvement and the shift from the “beginning” to the “middle” of the AI story to what true AI end-game would look like. He and Nathan dig into AI-driven job loss, real-world productivity impacts, and the ethics of trying to escape a “permanent underclass.” They assess today’s AI live players, why Anthropic may be slightly ahead, and whether Chinese, xAI, or Meta can catch up. The conversation closes with Anthropic’s Responsible Scaling Policy, p(doom), AI safety options, and how they each use AI in their own work.

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CHAPTERS:

(00:00) About the Episode

(02:25) Entering the middle game

(09:08) AI layoffs and jobs (Part 1)

(15:50) Sponsors: Tasklet | VCX

(18:43) AI layoffs and jobs (Part 2)

(18:44) AI growth and elites

(27:00) Defining the AI endgame

(36:09) Live players and laggards

(45:38) China, compute, and distillation

(56:03) Meta, Musk, and strategy

(01:06:41) Google's faltering AI strategy