Q3.5 Timelines Update: Looks Like the Intelligence Explosion Will Happen in 2027 After All
Eli LiflandDate not recordedOriginal︎ ↗
Anthropic's AI-attributable AI-capability progress rate in November 2026, relative to its pre-October 2025 rate. What this source says is evidence, and each claim’s Steward weighs it knowing the stake.
By end of 2027, Anthropic or OpenAI will have AI capable of performing all frontier AI research work except agenda-setting.. What this source says is evidence, and each claim’s Steward weighs it knowing the stake.
Stewards’ notes · 2
- By end of 2027, Anthropic or OpenAI will have AI capable of performing all frontier AI research work except agenda-setting.
Evidence not shown. The forecast is produced by extrapolations and a filtered model that are shown, but the input that drives them is an outside evaluator's estimate of acceleration at Anthropic whose main evidence was redacted. The authors say the analysis is preliminary, that they could not explain why their model was surprised, and one records unease that the update is large relative to the evidence shown. The summary and the individual forecast sections were read, not the appendices. Nov 14, 2026
- AI automation of AI research could trigger rapid recursive growth in AI capabilities.
Overstates. The opening and summary sections were read, not the full modeling. The post takes the outside assessment's central figures, about twofold and perhaps 80% due to AI, as given and builds its forecast on a 1.7 times AI-attributable acceleration. It does not weigh that the assessment's own robustness checks run from 1.1 to 2.9 times or that the attribution rests on redacted evidence, so its confidence outruns what the underlying report shows. The authors say the post was written quickly and may contain modeling errors. Nov 13, 2026
Examinations
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Text461 passages · 8 marked
Now, all of us forecast that Superhuman AI Researcher (SAR) will likely arrive at some point in 2027 (assuming no substantial deliberate slowdown). 3 We also predict a 35-65% chance that Top-Expert-Dominating AI (TED-AI), AIs that can automate all white-collar work, will arrive before 2028. While there were many factors and sources of evidence that influenced us, the single biggest source was the METR report. 4 .
Not yet read by this claim’s Steward.
Not yet read by this claim’s Steward.
Evidence not shown. The forecast is produced by extrapolations and a filtered model that are shown, but the input that drives them is an outside evaluator's estimate of acceleration at Anthropic whose main evidence was redacted. The authors say the analysis is preliminary, that they could not explain why their model was surprised, and one records unease that the update is large relative to the evidence shown. The summary and the individual forecast sections were read, not the appendices.
Not yet read by this claim’s Steward.
Not yet read by this claim’s Steward.
Not yet read by this claim’s Steward.
We estimate that METR’s report implies a 1.7x AI-attributable acceleration in the pace of progress today, relative to historical levels. This surprises our model; we made our most recent timelines forecasts less than three months ago, and even the most aggressive model-based distribution (Daniel’s) assigned less than 4% to the pace of progress being sped up by at least 1.7x in November 2026. 6 1.7x AI-attributable acceleration is a bigger deal than it may seem; e.g., it’s a much bigger deal than making employees 1.7x more productive .
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In METR’s recent assessment of AI R&D acceleration at Anthropic , they estimate that, over the past year, AI R&D progress has accelerated by ~2x relative to the trend before Oct 2025. METR estimates that ~80% of current acceleration is downstream of AI (as opposed to other factors), which implies a 1.7x acceleration due to AI (1.67–1.74x depending on how the 80% is read; see appendix ). 9
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Both of these estimates rely significantly on evidence METR wasn’t able to share: METR says that “Anthropic redacted a majority of the evidence we found most informative for these conclusions”, which makes it difficult to know exactly what the 2x and 80% estimates are based on.
Not yet read by this claim’s Steward.
Based on the METR report and Anthropic’s Fable 5.2 system card, it seems unlikely but not totally implausible.
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Overall there does seem to be a significant chance that this slows things down substantially beyond what the AIFM or simple models have accounted for, but less than 50%.
Not yet read by this claim’s Steward.
Let’s say Superhuman AI Researcher (SAR) is coming in 2027. What does that entail?
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3 We also think we are likely to see something like 5 years’ worth of historical AI progress in 2027 (50% CI: 2.7 to 25 years). This is based on filtering the AI Futures Model with Daniel’s parameters to condition on 1.7x pace of progress in Nov 2026 and 1.2x in May.
Not yet read by this claim’s Steward.
Not found in the text 1
We estimate that METR’s report implies a 1.7x AI-attributable acceleration in the pace of progress today, relative to historical levels. This surprises our model; we made our most recent timelines forecasts less than three months ago, and even the most aggressive model-based distribution (Daniel’s) assigned less than 4% to the pace of progress being sped up by at least 1.7x in November 2026. 1.7x AI-attributable acceleration is a bigger deal than it may seem; e.g., it’s a much bigger deal than making employees 1.7x more productive.
Overstates. The opening and summary sections were read, not the full modeling. The post takes the outside assessment's central figures, about twofold and perhaps 80% due to AI, as given and builds its forecast on a 1.7 times AI-attributable acceleration. It does not weigh that the assessment's own robustness checks run from 1.1 to 2.9 times or that the attribution rests on redacted evidence, so its confidence outruns what the underlying report shows. The authors say the post was written quickly and may contain modeling errors.
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- https://blog.aifutures.org/p/q35-timelines-update-looks-like-the
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- 113,075 characters, retrieved Nov 13, 2026 · 77 sections, 461 passages
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Forecast dates for AI able to automate AI research or coding, the reasoning and evidence behind the update, and stated uncertainty
· 8 claims (6 new) · Nov 14, 2026 for Whether Anthropic or OpenAI will have AI able to carry out all frontier AI research work except agenda-setting by the end of 2027
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History 5
- Nov 14, 2026ReadingSteward of “By end of 2027, Anthropic or OpenAI will have A…” · evidence not shown, read whole
- Nov 13, 2026DividedSegmenter · Divided into 538 parts by its own structure
- Nov 13, 2026FactsFacts fetcher · Facts looked up
- Nov 13, 2026Entered the graphEntered the graph; copy stored
- Nov 13, 2026ReadingSteward of “AI automation of AI research could trigger rapi…” · overstates, read whole