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← Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it.
17 connected korrents · 14 moments from 15 Jul 2021 to 22 Sept 2026.
Everything filed under AI and science
AI and science
Everything filed under LLMs
LLMs
Everything filed under mathematics
mathematics
Everything filed under protein structure prediction
protein structure prediction
Everything filed under recursive self-improvement
recursive self-improvement
Everything filed under AGI
AGI Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it. Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it. Last stated 2 years ago
19 Sept 2024
DL
Derek Lowe — holds since 2024-09-19 — tap for who they are
Same subject: Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew. — tap to centre the map on it Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew. Last stated a year ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: How much machine learning can help a biological problem is set by the quality of the data around that problem, not by the algorithms. — tap to centre the map on it 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 2 years ago
19 Sept 2024
DL
Derek Lowe — holds since 2024-09-19 — tap for who they are
Same subject: Machine learning is a shallow field compared with mathematics: even its most important ideas can be explained in a couple of minutes. — tap to centre the map on it Machine learning is a shallow field compared with mathematics: even its most important ideas can be explained in a couple of minutes. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: Alignment of today's models is going well enough to look solvable, while aligning models we can no longer understand remains unsolved. — tap to centre the map on it Alignment of today's models is going well enough to look solvable, while aligning models we can no longer understand remains unsolved. Last stated 9 months ago
22 Jan 2026
JL
Jan Leike — holds since 2026-01-22 — tap for who they are
Same subject: Model intelligence should speciate like the animal kingdom rather than converge on one oracle that knows everything. — tap to centre the map on it Model intelligence should speciate like the animal kingdom rather than converge on one oracle that knows everything. Last stated 7 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: Most proteins have no known function, so there is no pile of solid data for a model to learn most of cell biology from. — tap to centre the map on it 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 2 years ago
19 Sept 2024
DL
Derek Lowe — holds since 2024-09-19 — tap for who they are
Same subject: A model can make an existing algorithm a hundred times faster and still cannot invent a better one, however long you give it. — tap to centre the map on it A model can make an existing algorithm a hundred times faster and still cannot invent a better one, however long you give it. Last stated 4 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: The current capabilities of existing AI models are barely being used and are often not even well understood. — tap to centre the map on it The current capabilities of existing AI models are barely being used and are often not even well understood. Last stated a month ago
18 Sept 2026
EM
Ethan Mollick — holds since 2026-09-18 — tap for who they are
Same subject: 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. — tap to centre the map on it 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 3 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility. — tap to centre the map on it Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence. — tap to centre the map on it Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence. Last stated a year ago
29 Jun 2025
EH
Elliot Hershberg — holds since 2025-06-29 — tap for who they are
Same subject: A persistently rising dividend yield eventually forces capital appreciation as the market rerates the stock. — tap to centre the map on it A persistently rising dividend yield eventually forces capital appreciation as the market rerates the stock. Last stated 8 months ago
3 Mar 2026
SB
Sanjay Bakshi — holds since 2026-03-03 — tap for who they are
Same subject: A proof and an explanation are different things, and a theorem can stay an unsolved expository problem long after it is proved. — tap to centre the map on it A proof and an explanation are different things, and a theorem can stay an unsolved expository problem long after it is proved. Last stated 4 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: 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. — tap to centre the map on it 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 4 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: 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. — tap to centre the map on it 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 4 weeks ago
22 Sept 2026
TC
Tyler Cowen — holds since 2026-09-22 — tap for who they are
Same subject: AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started. — tap to centre the map on it 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 months ago
3 Aug 2026
CP
Chamath Palihapitiya — holds since 2026-08-03 — tap for who they are
Same subject: AI research will be fully automated around 2030 or 2031, and AI will beat humans at essentially any job by about 2033. — tap to centre the map on it AI research will be fully automated around 2030 or 2031, and AI will beat humans at essentially any job by about 2033. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
At the centre
Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it.
Holds Read this korrent →
Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew.
Holds
How much machine learning can help a biological problem is set by the quality of the data around that problem, not by the algorithms.
Holds
Machine learning is a shallow field compared with mathematics: even its most important ideas can be explained in a couple of minutes.
Holds
Alignment of today's models is going well enough to look solvable, while aligning models we can no longer understand remains unsolved.
Holds
Model intelligence should speciate like the animal kingdom rather than converge on one oracle that knows everything.
Holds
Most proteins have no known function, so there is no pile of solid data for a model to learn most of cell biology from.
Holds
A model can make an existing algorithm a hundred times faster and still cannot invent a better one, however long you give it.
Holds
The current capabilities of existing AI models are barely being used and are often not even well understood.
Holds
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.
Holds
Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility.
Holds
Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence.
Holds
A persistently rising dividend yield eventually forces capital appreciation as the market rerates the stock.
Holds
A proof and an explanation are different things, and a theorem can stay an unsolved expository problem long after it is proved.
Holds
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.
Holds
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.
Holds
AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started.
Holds
AI research will be fully automated around 2030 or 2031, and AI will beat humans at essentially any job by about 2033.
Holds