Really fun to hang again with my friend ๐
@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