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AI Futures Timelines and Takeoff Model: Dec 2025 Update

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Authors

elifland·bhalstead·Alex Kastner·Daniel Kokotajlo

Credibility Rating

3/5
Good(3)

Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.

Rating inherited from publication venue: LessWrong

A LessWrong post providing a quantitative update to an AI timelines and takeoff model, useful for those tracking capability forecasts and debating the pace of transformative AI development as of late 2025.

Forum Post Details

Karma
144
Comments
34
Forum
lesswrong
Forum Tags
AI

Metadata

Importance: 62/100blog postanalysis

Summary

A December 2025 update to a quantitative model forecasting AI capability milestones, including full coding automation and ASI. Compared to prior estimates, the model extends timelines to full coding automation by approximately 3-5 years due to more conservative assumptions about AI R&D self-acceleration. The authors advocate for transparent, explicit modeling as a tool for reasoning about AI development trajectories.

Key Points

  • Updated model predicts full coding automation 3-5 years later than previous 2027 estimates, driven by conservative AI R&D speedup assumptions.
  • Key milestones tracked include full coding automation and artificial superintelligence (ASI), with explicit probabilistic forecasts.
  • The model blends empirical data with intuitive parameter estimates, and authors are transparent about this hybrid methodology.
  • Explicit quantitative modeling is argued to be more useful than informal forecasting for preparing for transformative AI outcomes.
  • More conservative pre-automation R&D speedup assumptions are the primary driver of timeline revisions.

Cited by 1 page

PageTypeQuality
AI TimelinesConcept95.0

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HTTP 200Fetched Feb 26, 20261377 KB
x This website requires javascript to properly function. Consider activating javascript to get access to all site functionality. AI Futures Timelines and Takeoff Model: Dec 2025 Update — LessWrong AI Frontpage 2025 Top Fifty: 14 % 144 AI Futures Timelines and Takeoff Model: Dec 2025 Update by elifland , bhalstead , Alex Kastner , Daniel Kokotajlo 31st Dec 2025 AI Alignment Forum 30 min read 34 144 Ω 47 We’ve significantly upgraded our timelines and takeoff model! It predicts when AIs will reach key capability milestones: for example, Automated Coder / AC (full automation of coding) and superintelligence / ASI (much better than the best humans at virtually all cognitive tasks). This post will briefly explain how the model works, present our timelines and takeoff forecasts, and compare it to our previous ( AI 2027 ) models (spoiler: the AI Futures Model predicts longer timelines to full coding automation than our previous model by about 3-5 years, in significant part due to being less bullish on pre-full-automation AI R&D speedups). Added Jan 2026: see here for clarifications regarding how our forecasts have changed since AI 2027. If you’re interested in playing with the model yourself, the best way to do so is via this interactive website: aifuturesmodel.com . If you’d like to skip the motivation for our model to an explanation for how it works, go here , The website has a more in-depth explanation of the model (starts here ; use the diagram on the right as a table of contents), as well as our forecasts . Why do timelines and takeoff modeling? The future is very hard to predict. We don't think this model, or any other model, should be trusted completely. The model takes into account what we think are the most important dynamics and factors, but it doesn't take into account everything. Also, only some of the parameter values in the model are grounded in empirical data; the rest are intuitive guesses. If you disagree with our guesses, you can change them above. Nevertheless, we think that modeling work is important. Our overall view is the result of weighing many considerations, factors, arguments, etc.; a model is a way to do this transparently and explicitly, as opposed to implicitly and all in our head. By reading about our model, you can come to understand why we have the views we do, what arguments and trends seem most important to us, etc. The future is uncertain, but we shouldn’t just wait for it to arrive. If we try to predict what will happen, if we pay attention to the trends and extrapolate them, if we build models of the underlying dynamics, then we'll have a better sense of what is likely, and we'll be less unprepared for what happens. We’ll also be able to better incorporate future empirical data into our forecasts. In fact, the improvements we’ve made to this model, as compared to our timelines model at the time we published AI 2027 (Apr 2025), have resulted in a roughly 3-5 year shift in our median for full coding

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Resource ID: a1c863df9c0fa30c | Stable ID: ZTE4NTFhNm