A simpler AI timelines model predicts 99% AI R&D automation in ~2032

At current rates of compute growth and algorithmic progress, this model’s median prediction is >99% automation of AI R&D in late 2032. Most simulations result in a 1000x to 10,000,000x increase in AI efficiency and 300x-3000x research output by 2035. I therefore suspect that existing trends in compute growth and automation will still produce extremely powerful AI on “medium” timelines, even if the full coding automation and superhuman research taste that drive the AIFM’s “fast” timelines (superintelligence by ~mid-2031) don’t happen.

In particular, the “doubling difficulty growth factor”, which measures whether time horizon increases superexponentially, could change the date of automated coder from 2028 to 2049! I suspect that time horizon is too poorly defined to nail down this parameter, and rough estimates of more direct AI capability metrics like uplift can give much tighter confidence intervals.

f was between 0.25-0.5 in Jan 2026, implying between 1.33x and 2x uplift. This informs the value of $E_{hac}$.

The AI Futures model is complex, but its conclusions are fairly robust to simplifications.

The median date of 99% automation is mid-2032. However, I don’t put too much weight on the exact predicted timelines because I haven’t thought much about the exact parameter values.

A basic sensitivity analysis shows that higher beta (diminishing returns) and lower v (automation velocity) make 99% automation happen later, and the other parameters don’t affect things much.

From playing around with this and other variations to the AI Futures model I think any reasonable timelines model will predict superhuman AI researchers before 2036 unless AI progress hits a wall or is deliberately slowed.