Bored in the AGI Era

New models keep dropping, but do they change anything? Jacob explains why he's checked out. Igor argues it's worth tracking where the storyline and the evidence diverge. They cover Astra vs. Fable, the AGI claims, labs moving the benchmarks, cheap models catching up, what inference really costs, disputed math results, and why looped transformers worry people who care about monitorability. They close with IPO rumors, data center backlash, and the politics of the winter ahead.

Chapters

(00:00) - Intro

(00:23) - Why We're Bored of Model Drops

(08:26) - AGI Claims and Moving Benchmarks

(15:56) - Sold vs. Delivered

(19:16) - IPOs and the Cost of Inference

(25:06) - Astra, Math Claims, and Looped Transformers

(31:11) - Winter Predictions

(39:44) - Outro

Critical Links

Below are the most important links for this episode. For more, visit the episode page on Kairos.fm.ARC Prize blogpost - OpenAI's GPT-6 Astra on ARC-AGI-3One Useful Thing blogpost - Centaurs and Cyborgs on the Jagged FrontierMETR report - OpenAI–Hugging Face incident investigationFortune article - OpenAI says it cracked Navier-Stokes, one of math's grand challengesCNBC article - OpenAI confidentially files for IPO, prepping Wall Street for mega AI debutFortune article - Hyperscalers hold $662 billion in data center commitments off balance sheetGoogle paper - Measuring the environmental impact of delivering AI at Google ScaleAxios article - Data center uproar scrambles the midterm election