Tl;dr: Our timelines haven’t changed much (they got slightly shorter) but our modeling and evidence base have noticeably improved, so we feel somewhat more confident.

Summary

We intend to regularly update our AI timelines forecasts as new evidence comes in and new analyses are done. Today's “Q2” update was delayed by the crunch to publish AI 2040: Plan A, our domestic regulation blog post, and the time needed to implement and document changes to our model.

The original AI Futures Model predicted when Automated Coder (AC), an AI for which the leading AI company would rather fire its human software engineers than forego AI usage for coding, would happen using METR's measurements of coding time horizon. (More precisely, time horizon anchors are used to set the effective compute required for AC.) While serviceable, this method has huge weaknesses, including (a) it's unclear what time horizon corresponds to AC (it's even unclear whether any finite value would) (b) people strongly disagree about the extent to which we should expect the time horizon trend to be superexponential as a function of effective compute, in a way that can lead to vastly different predictions.