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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 on record from 28 Oct 2011 to 16 Sept 2026.
Everything filed under AI alignment
AI alignment
Everything filed under protein structure prediction
protein structure prediction
Everything filed under mathematics
mathematics
Everything filed under AI and science
AI and science
Everything filed under AI sentience
AI sentience
Everything filed under semiconductors
semiconductors
Everything filed under team size
team size
Everything filed under data centers
data centers 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 5 days 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 weeks ago
6 Sept 2026
JP
Jakub Pachocki — holds since 2026-09-06 — 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 a month 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 2 months ago
16 Jul 2026
SJ
Steven Johnson — holds since 2026-07-16 — tap for who they are
Same subject: Semiconductor infrastructure has not kept up with AI's growth, and closing that gap needs capacity built in unconventional ways. — tap to centre the map on it Semiconductor infrastructure has not kept up with AI's growth, and closing that gap needs capacity built in unconventional ways. Last stated 3 months ago
18 Jun 2026
LT
Lip-Bu Tan — holds since 2026-06-18 — tap for who they are
Same subject: 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. — tap to centre the map on it 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 2 years ago
19 Sept 2024
DL
Derek Lowe — holds since 2024-09-19 — tap for who they are
Same subject: Progress in AI takes a very strong dozen or two researchers, not hundreds or thousands of them. — tap to centre the map on it Progress in AI takes a very strong dozen or two researchers, not hundreds or thousands of them. Last stated 3 months ago
10 Jun 2026
MZ
Mark Zuckerberg — holds since 2026-06-10 — tap for who they are
Same subject: Labour is a huge constraint on the AI build-out, and the way round it is to build data centres as modules in Asian factories rather than on site. — tap to centre the map on it Labour is a huge constraint on the AI build-out, and the way round it is to build data centres as modules in Asian factories rather than on site. Last stated 6 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail. — tap to centre the map on it A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail. Last stated 2 years ago
7 May 2024
BS
Buck Shlegeris — holds since 2024-05-07 — tap for who they are
Same subject: A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean. — tap to centre the map on it A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean. Last stated 10 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A model may have a worldview of its own, but it can never be placed above a person under any circumstance. — tap to centre the map on it A model may have a worldview of its own, but it can never be placed above a person under any circumstance. Last stated 4 months ago
3 Jun 2026
KH
Kelsey Hightower — holds since 2026-06-03 — 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 2 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: Existing protein structure prediction methods fall far short of atomic accuracy when no homologous structure is available. — tap to centre the map on it Existing protein structure prediction methods fall far short of atomic accuracy when no homologous structure is available. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — 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 3 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 3 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: Academic credentials — grades, major, the prestige of the degree — barely matter to industry hiring. — tap to centre the map on it Academic credentials — grades, major, the prestige of the degree — barely matter to industry hiring. Last stated 15 years ago
28 Oct 2011
PM
Patrick McKenzie — holds since 2011-10-28 — 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
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
Semiconductor infrastructure has not kept up with AI's growth, and closing that gap needs capacity built in unconventional ways.
Holds
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.
Holds
Progress in AI takes a very strong dozen or two researchers, not hundreds or thousands of them.
Holds
Labour is a huge constraint on the AI build-out, and the way round it is to build data centres as modules in Asian factories rather than on site.
Holds
A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail.
Holds
A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean.
Holds
A model may have a worldview of its own, but it can never be placed above a person under any circumstance.
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
Existing protein structure prediction methods fall far short of atomic accuracy when no homologous structure is available.
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
Academic credentials — grades, major, the prestige of the degree — barely matter to industry hiring.
Holds