Forecast track records favor Kokotajlo's AGI timelines over critics, argues Manheim
davidmanheim · x · 2026-11-11
davidmanheim defends AI 2027 author Daniel Kokotajlo against Ramez's criticism: "models and forecasts are hypotheses," testable against data, and Kokotajlo's "insanely good" forecasting track record — including assumptions held before deep learning took off — makes his AGI timelines empirically more credible than Ramez's 11-year-old views. The clash centers on using track records as the evidence base for judging short-AGI-timeline forecasts.
Related event: Debate Erupts Over Reliability of Kokotajlo's AI Forecasts(3 posts)→
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