๊ฐ€์ž… ํ›„ ์ดˆ๋Œ€ ๋งํฌ๋ฅผ ๊ณต์œ ํ•˜๋ฉด ๋™์˜์ƒ ์žฌ์ƒ ๋ฐ ์ดˆ๋Œ€ ๋ณด์ƒ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

sarah guo
@saranormous
startup investor/helper, founder @conviction. interested in intelligence, accelerating progress. tech podcast: @nopriorspod
๊ฐ€์ž… July 2011
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Really fun to hang again with my friend ๐Ÿƒ @polynoamial (OpenAI research scientist, our first guest ever on @NoPriorsPod in early 2023) to talk about the implications of large test-time compute, and what happens when models are given $10M budgets to spend on a single task. Topics: 01:23 โ€“ Why Benchmarks Are Broken 04:19 โ€“ Compute Budgets and Projections 06:48 โ€“ How Long Should Models Think? 08:01 โ€“ Benchmarkmaxxing 09:48 โ€“ Noam's Evals 12:40 โ€“ Safety (When Model Capability Scales With Spend) 16:09 โ€“ Implications For the Model Release Cycle 18:34 โ€“ Latent Model Capability 22:27 โ€“ Limits on Recursive Self-Improvement 28:38 โ€“ Large-Scale Multi-Agent Coordination 30:39 โ€“ Competition at the Frontier 33:19 โ€“ Breaking the Benchmark Grid Equilibrium 34:57 โ€“ Why Benchmarks Should be Scaled by Cost
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