Yuchen Jin @Yuchenj_UW
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