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← AI-assisted biological research still depends on physical wet-lab work that remains a necessary bottleneck for now.
17 connected korrents · 16 moments from 15 Jul 2021 to 29 Oct 2026.
Everything filed under AI and science
AI and science
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 AI alignment
AI alignment
Everything filed under AI writing
AI writing
Everything filed under AI sentience
AI sentience 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: AI-assisted biological research still depends on physical wet-lab work that remains a necessary bottleneck for now. AI-assisted biological research still depends on physical wet-lab work that remains a necessary bottleneck for now. Last stated 2 months ago
16 Sept 2026
KJ
Katelyn Jetelina — holds since 2026-09-16 — tap for who they are
Same subject: Not every bottleneck on medical progress is one AI can remove, and which ones will remain can be guessed at now. — tap to centre the map on it Not every bottleneck on medical progress is one AI can remove, and which ones will remain can be guessed at now. Last stated a year ago
2 Aug 2025
JT
Jacob Trefethen — holds since 2025-08-02 — tap for who they are
Same subject: Confidence in monitoring, not capability research, will become the binding constraint on AI progress. — tap to centre the map on it Confidence in monitoring, not capability research, will become the binding constraint on AI progress. Last stated 2 months ago
6 Sept 2026
JP
Jakub Pachocki — holds since 2026-09-06 — tap for who they are
Same subject: Agentic AI systems for autonomously carrying out scientific research are still at a very early stage of development. — tap to centre the map on it Agentic AI systems for autonomously carrying out scientific research are still at a very early stage of development. Last stated 5 months ago
21 Jun 2026
EH
Elliot Hershberg — holds since 2026-06-21 — tap for who they are
Same subject: Current scientific publication systems may be unable to handle the increasing volume of work produced by AI. — tap to centre the map on it Current scientific publication systems may be unable to handle the increasing volume of work produced by AI. Last stated 9 months ago
19 Feb 2026
LP
Lior Pachter — holds since 2026-02-19 — tap for who they are
Same subject: 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. — tap to centre the map on it 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 a month ago
22 Sept 2026
NL
Nathan Lambert — holds since 2026-09-22 — tap for who they are
Same subject: AI's bottleneck was never its algorithms but how little data they were fed, which is why the field needed ImageNet rather than another model. — tap to centre the map on it AI's bottleneck was never its algorithms but how little data they were fed, which is why the field needed ImageNet rather than another model. Last stated 3 months ago
10 Aug 2026
FL
Fei-Fei Li — holds since 2026-08-10 — tap for who they are
Same subject: Current AI systems are very unlikely to be close to achieving genuine sentience. — tap to centre the map on it Current AI systems are very unlikely to be close to achieving genuine sentience. Last stated 4 months ago
16 Jul 2026
SJ
Steven Johnson — holds since 2026-07-16 — tap for who they are
Same subject: AI is about to usher in a golden age of rapid scientific discovery — tap to centre the map on it AI is about to usher in a golden age of rapid scientific discovery Last stated a week ago
29 Oct 2026
NS
Noah Smith — holds since 2026-10-29 — 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 a month ago
22 Sept 2026
TC
Tyler Cowen — holds since 2026-09-22 — tap for who they are
Same subject: A sealed machine that redesigns itself will eventually redesign everything that touches its seal. — tap to centre the map on it A sealed machine that redesigns itself will eventually redesign everything that touches its seal. Last stated 2 weeks ago
21 Oct 2026
BM
Bruno Maçães — holds since 2026-10-21 — 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
At the centre
AI-assisted biological research still depends on physical wet-lab work that remains a necessary bottleneck for now.
Holds Read this korrent →
Not every bottleneck on medical progress is one AI can remove, and which ones will remain can be guessed at now.
Holds
Confidence in monitoring, not capability research, will become the binding constraint on AI progress.
Holds
Agentic AI systems for autonomously carrying out scientific research are still at a very early stage of development.
Holds
Current scientific publication systems may be unable to handle the increasing volume of work produced by AI.
Holds
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.
Holds
AI's bottleneck was never its algorithms but how little data they were fed, which is why the field needed ImageNet rather than another model.
Holds
Current AI systems are very unlikely to be close to achieving genuine sentience.
Holds
AI is about to usher in a golden age of rapid scientific discovery
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
A sealed machine that redesigns itself will eventually redesign everything that touches its seal.
Holds
AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started.
Holds