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← Deep learning is not yet ready for the task that would actually add…
17 connected korrents · 16 moments from 3 Sept 2015 to 7 Sept 2026.
Everything filed under AI and science
AI and science
Everything filed under neural networks
neural networks
Everything filed under protein structure prediction
protein structure prediction
Everything filed under AI alignment
AI alignment
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design
Everything filed under LLMs
LLMs 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: Deep learning is not yet ready for the task that would actually add value in drug development: predicting safety and efficacy in humans. Deep learning is not yet ready for the task that would actually add value in drug development: predicting safety and efficacy in humans. Last stated 3 years ago
23 Dec 2023
AT
Alex Telford — holds since 2023-12-23 — tap for who they are
Same subject: We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often. — tap to centre the map on it We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often. Last stated 3 years ago
25 May 2023
DL
Derek Lowe — holds since 2023-05-25 — tap for who they are
Same subject: The human data an AI model would need to predict trial outcomes can only come from trials in people, so the loop runs no faster than the trials themselves. — tap to centre the map on it The human data an AI model would need to predict trial outcomes can only come from trials in people, so the loop runs no faster than the trials themselves. Last stated 8 months ago
28 Feb 2026
RT
Ruxandra Teslo — holds since 2026-02-28 — tap for who they are
Same subject: A compound's AI origin story is not by itself a reason to expect it to do better in the clinic. — tap to centre the map on it A compound's AI origin story is not by itself a reason to expect it to do better in the clinic. Last stated 2 years ago
13 May 2024
DL
Derek Lowe — holds since 2024-05-13 — tap for who they are
Same subject: Deep learning will be understood very differently in thirty years than it is today. — tap to centre the map on it Deep learning will be understood very differently in thirty years than it is today. Last stated 11 years ago
3 Sept 2015
CO
Christopher Olah — holds since 2015-09-03 — 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: Better drug candidates do not shorten clinical trials, because a trial's duration is set by operational and regulatory friction rather than by how good the drug is. — tap to centre the map on it Better drug candidates do not shorten clinical trials, because a trial's duration is set by operational and regulatory friction rather than by how good the drug is. Last stated 8 months ago
28 Feb 2026
RT
Ruxandra Teslo — holds since 2026-02-28 — tap for who they are
Same subject: Underestimating near-term AI progress is itself a danger, which is why researchers should register their forecasts in public. — tap to centre the map on it Underestimating near-term AI progress is itself a danger, which is why researchers should register their forecasts in public. Last stated 3 years ago
29 Aug 2023
AC
Ajeya Cotra — holds since 2023-08-29 — tap for who they are
Same subject: A compelling simulation of a human being could arrive within five years, and the technology is heading there whether or not it is a good idea. — tap to centre the map on it A compelling simulation of a human being could arrive within five years, and the technology is heading there whether or not it is a good idea. Last stated a year ago
30 Apr 2025
TS
Tim Sweeney — holds since 2025-04-30 — tap for who they are
Same subject: A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models. — tap to centre the map on it A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models. Last stated 8 years ago
11 Oct 2018
KT
Kristina Toutanova — holds since 2018-10-11 — tap for who they are
MC
Ming-Wei Chang — holds since 2018-10-11 — tap for who they are
KL
Kenton Lee — holds since 2018-10-11 — tap for who they are
JD
Jacob Devlin — holds since 2018-10-11 — tap for who they are
Same subject: A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable. — tap to centre the map on it A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable. Last stated 11 years ago
10 Dec 2015
JS
Jian Sun — holds since 2015-12-10 — tap for who they are
KH
Kaiming He — holds since 2015-12-10 — tap for who they are
Same subject: A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression. — tap to centre the map on it A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression. Last stated 2 months ago
7 Sept 2026
KK
Kevin Kelly — holds since 2026-09-07 — tap for who they are
Same subject: A small enough winning ticket learns faster than the network it was cut out of, and ends up more accurate than it. — tap to centre the map on it A small enough winning ticket learns faster than the network it was cut out of, and ends up more accurate than it. Last stated 9 years ago
9 Mar 2018
MC
Michael Carbin — holds since 2018-03-09 — tap for who they are
JF
Jonathan Frankle — holds since 2018-03-09 — tap for who they are
Same subject: A winning ticket wins on its initial weights: the connections it keeps started at values that happen to make training work. — tap to centre the map on it A winning ticket wins on its initial weights: the connections it keeps started at values that happen to make training work. Last stated 9 years ago
9 Mar 2018
MC
Michael Carbin — holds since 2018-03-09 — tap for who they are
JF
Jonathan Frankle — holds since 2018-03-09 — tap for who they are
Same subject: Intelligence is the execution of small, simplicity-weighted programs found by search over smooth loss landscapes in overparameterized networks, approaching Bayes-optimal reasoning as scale increases. — tap to centre the map on it Intelligence is the execution of small, simplicity-weighted programs found by search over smooth loss landscapes in overparameterized networks, approaching Bayes-optimal reasoning as scale increases. Last stated 5 years ago
11 Jun 2021
GW
Gwern — holds since 2021-06-11 — 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
At the centre
Deep learning is not yet ready for the task that would actually add value in drug development: predicting safety and efficacy in humans.
Holds Read this korrent →
We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often.
Holds
The human data an AI model would need to predict trial outcomes can only come from trials in people, so the loop runs no faster than the trials themselves.
Holds
A compound's AI origin story is not by itself a reason to expect it to do better in the clinic.
Holds
Deep learning will be understood very differently in thirty years than it is today.
Holds
Confidence in monitoring, not capability research, will become the binding constraint on AI progress.
Holds
Better drug candidates do not shorten clinical trials, because a trial's duration is set by operational and regulatory friction rather than by how good the drug is.
Holds
Underestimating near-term AI progress is itself a danger, which is why researchers should register their forecasts in public.
Holds
A compelling simulation of a human being could arrive within five years, and the technology is heading there whether or not it is a good idea.
Holds
A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models.
Holds
A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable.
Holds
A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression.
Holds
A small enough winning ticket learns faster than the network it was cut out of, and ends up more accurate than it.
Holds
A winning ticket wins on its initial weights: the connections it keeps started at values that happen to make training work.
Holds
Intelligence is the execution of small, simplicity-weighted programs found by search over smooth loss landscapes in overparameterized networks, approaching Bayes-optimal reasoning as scale increases.
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