Ben Todd: the biggest question in AI is whether acceleration extends beyond verifiable tasks
ben_j_todd · x · 2026-11-07
Ben Todd frames what he calls the biggest question in AI: does the current acceleration only apply to verifiable tasks and thus quickly peter out, or are non-verifiable tasks improving rapidly too, just slightly behind? He bets on the latter. His accompanying graphic explains the "verifiability bottleneck" model, where a trend break in capabilities occurs but plateaus rather than leading to runaway progress.
More from AGI Musings
- AI central planning revisited: markets still produce demand signals models can't replace — NathanpmYoung · 2026-11-08
- AI safety circle memes shared 'terror' over METR report via Hubinger pfp — danfaggella · 2026-11-07
- Proposal: freeze frontier AI capability, redistribute compute to cheap inference — austinc3301 · 2026-11-07
- Kundaje: Even After Validation, Delivering AAV/CRISPR to Causal Cell Types Remains Unsolved — anshulkundaje · 2026-11-07
- Stanford Prof: Once LLMs Can Act on Noncoding Variants, Validation Becomes the Bottleneck — anshulkundaje · 2026-11-07
- Demis Hassabis: one AI-savvy person can outperform a startup team; 1/10 headcount in 5 years — smtabatabaie · 2026-11-07