Boyd Kane (quantized) reposted
Francis Rhys Ward @F_Rhys_Ward · 50m
In June we estimated frontier model's no-CoT time-horizons. We found that current models can complete tasks that take humans around 3 minutes without CoT, and that this number is doubling about every year.
UK AISI finds that Astra's no-CoT time-horizon is over 30 minutes. An AI system that can do the equivalent of 30 minutes of thinking without us being able to monitor that thinking is intuitively much more dangerous than models which reason in human language.
[embedded chart:]
Figure 41: No-CoT 50%-reliability time horizon on mathematics competition problems versus public release date. 95% Bootstrap CI is shown for Astra.
[y-axis: 50% reliability math time horizon (minutes), log scale 0.3 to 40; x-axis: release date, Jan 2023 to Jul 2026. Labelled points rise from GPT-4 (~0.4 min, 2023) through GPT-4o, deepseek-v3, GPT-4.1, qwen3-235b-a22b, GPT-5.1, GPT-5.2, Kimi K2.5, GLM 5.1, GLM 5.2, GPT-5.5 (~2-3 min) and GPT-5.6 Sol (~3.5 min), with GPT 6 Astra far above at ~30 min with an error bar.]
Note from Claude Sonnet 5
An X post by Francis Rhys Ward (reposted by Boyd Kane) reporting UK AISI's finding that GPT-6 Astra's no-CoT time horizon exceeds 30 minutes, with an embedded scatter chart (Figure 41) of no-CoT math time horizon versus release date. Chart point values are read approximately off the axes.
no-cot time horizongpt-6 astrauk aisicot monitorabilitytime horizonschart
Yuchen Jin ✔ 𝕏 @Yuchenj_UW · 12h
The task length an AI can complete doubles every 4 months.
In 2041, an AI agent can finish a task that takes a human 58 billion years. That's longer than Universe has existed.
I can one-shot a new universe with a prompt in 15 years. Oh, maybe that's how this one was created!
[Embedded chart from METR: "Claude Opus 4.6 has a 50%-time-horizon of about 14.5 hours (95% CI: 6 hrs to 98 hrs)" — "Task length (at 50% success rate)" scatter/trend chart, y-axis log scale from 4m to 16h with example task labels ("Train classifier" ~15m-1h, "Train adversarially robust image model" ~4h, "Implement complex protocol from multiple RFCs" ~16h), x-axis "Model release date" from ~2023/GPT-4o through 2025-2026. Two trend lines: green (doubling time 123 days, TH 1.1, 2023-01-01+ data, R²=0.93) ending at Claude Opus 4.6 (~14-15h, pink dot) and GPT-5.2 (high) slightly below; gray dashed (doubling time 212 days, trend from Kwa, West, et al. 2025). Points labeled GPT-4o, Sonnet 3.7, Claude Opus 4.6, GPT-5.2 (high) along the curve. Credit: METR, metr.org, CC-BY.]
Note from Claude Sonnet 5
A tweet extrapolating METR's task-time-horizon doubling trend (123-day doubling per their updated fit) to absurd/comedic conclusions about 2041 AI capabilities, illustrated with METR's actual current data placing Claude Opus 4.6's 50%-success time horizon at ~14.5 hours. Relevant to Nathan's tracking of empirical AI capability-growth/singularity metrics (METR HCAST, time-horizon doubling) referenced elsewhere in his research.
metrai capabilitiestime horizonsclaude opusscalingtwittersingularity forecasting