17 connected korrents · 12 moments from 15 Jul 2021 to 22 Sept 2026.
At the centre
AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work.
Last stated 19 Sept 2024 · 2 years ago
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Derek Lowe
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Cannot both be true
Understanding the biological machine is about five years away, not ten.
Last stated 23 Mar 2026 · 7 months ago
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Jensen Huang
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Similar wording
Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence.
Last stated 29 Jun 2025 · a year ago
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Elliot Hershberg
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Similar wording
AI-assisted biological research still depends on physical wet-lab work that remains a necessary bottleneck for now.
Last stated 16 Sept 2026 · a month ago
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Katelyn Jetelina
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Similar wording
Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it.
Last stated 19 Sept 2024 · 2 years ago
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Derek Lowe
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Similar wording
The AI research cycle from idea to experiment will likely soon be 10x faster, but that may not make researchers 10x more productive in the field's net understanding.
Last stated 22 Sept 2026 · a month ago
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Nathan Lambert
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Similar wording
Most proteins have no known function, so there is no pile of solid data for a model to learn most of cell biology from.
Last stated 19 Sept 2024 · 2 years ago
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Derek Lowe
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Similar wording
A compound's AI origin story is not by itself a reason to expect it to do better in the clinic.
Last stated 13 May 2024 · 2 years ago
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Derek Lowe
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Similar wording
How much machine learning can help a biological problem is set by the quality of the data around that problem, not by the algorithms.
Last stated 19 Sept 2024 · 2 years ago
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Derek Lowe
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Similar wording
Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility.
Last stated 15 Jul 2021 · 5 years ago
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Demis Hassabis
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Same subject: protein structure prediction
A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next.
Last stated 30 Jul 2026 · 3 months ago
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Jeff Dean
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Same subject: protein structure prediction
Existing protein structure prediction methods fall far short of atomic accuracy when no homologous structure is available.
Last stated 15 Jul 2021 · 5 years ago
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Demis Hassabis
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Same subject: mathematics
A persistently rising dividend yield eventually forces capital appreciation as the market rerates the stock.
Last stated 3 Mar 2026 · 8 months ago
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Sanjay Bakshi
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Same subject: mathematics
A proof and an explanation are different things, and a theorem can stay an unsolved expository problem long after it is proved.
Last stated 30 Jun 2026 · 4 months ago
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Grant Sanderson
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Same subject: mathematics
A stream of AI-written papers with any error rate at all becomes insufferable, because finding the error costs more than the paper is worth even at ninety-nine percent.
Last stated 30 Jun 2026 · 4 months ago
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Grant Sanderson
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Same subject: recursive self-improvement
A ban on self-recursive improvement in AI models would create a big incentive for some other parts of the world to invest a lot more in compute.
Last stated 22 Sept 2026 · a month ago
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Tyler Cowen
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Same subject: recursive self-improvement
AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started.
Last stated 3 Aug 2026 · 3 months ago
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Chamath Palihapitiya
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Same subject: recursive self-improvement
AI research will be fully automated around 2030 or 2031, and AI will beat humans at essentially any job by about 2033.
Last stated 11 Aug 2026 · 2 months ago
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Ryan Greenblatt