Cotra

Article

Cotra is a recurring person in the Astral Codex Ten archive, appearing 2 times across 2 issues between February 12, 2026 and February 23, 2026. The archive places it in contexts such as “Cotra picked five intuitively compelling guesses (the namesake Bio Anchors)”; “Cotra’s estimate comes primarily from one paper”; “In Cotra’s defense, she admitted that this was the area where she was least certain”. It most often appears alongside Bio Anchors, 2010 kink, 2024 kink.

Metadata

  • Category: People
  • Mention count: 2
  • Issue count: 2
  • First seen: February 12, 2026
  • Last seen: February 23, 2026

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

February 12, 2026 · Original source
Ajeya Cotra’s Biological Anchors report was the landmark AI timelines forecast of the early 2020s. In many ways, it was prescient - it nailed the scaling hypothesis, predicted the current AI boom, and introduced concepts like “time horizons” that have entered common parlance. In most cases where its contemporaries challenged it, its assumptions have been borne out, and its challengers proven wrong.
But its headline prediction - an AGI timeline centered around the 2050s - no longer seems plausible. The current state of the discussion ranges from late 2020s to 2040s, with more remote dates relegated to those who expect the current paradigm to prove ultimately fruitless - the opposite of Ajeya’s assumptions. Cotra later shortened her own timelines to 2040 (as of 2022) and they are probably even shorter now.
Cotra asked: how quickly is the AI industry getting access to more compute / more FLOPs? And how many FLOPs would AGI take? If we can figure out both those things, determining the date of AGI arrival becomes a matter of simple division.
February 23, 2026 · Original source
Cotra estimated “~2.5 OOM worse [than the brain], +/- 1 OOM”, based on reference points like how much less efficient dialysis machines are than a human kidney, how much more efficient solar panels are than leaves, and the FLOP/watt efficiency of a V100 GPU. But most of those anchors had little to do with where ML algorithms were in 2020 when bioanchors was written, and would have given a very similar estimate for “present state of ML algorithms” 20 years earlier or 20 years later.