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← On small tasks he can check himself, he catches about as many of the AI's errors as it catches of his.
17 connected korrents · 13 moments from 15 Jul 2021 to 19 Oct 2026.
Everything filed under AI and science
AI and science
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AI alignment
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LLMs
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AI and jobs
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AI agents 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: On small tasks he can check himself, he catches about as many of the AI's errors as it catches of his. On small tasks he can check himself, he catches about as many of the AI's errors as it catches of his. Last stated 7 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — tap for who they are
Same subject: AI assistants still make mistakes and their answers need to be double-checked by a human. — tap to centre the map on it AI assistants still make mistakes and their answers need to be double-checked by a human. Last stated 2 months ago
9 Aug 2026
HR
Harper Reed — holds since 2026-08-09 — tap for who they are
Same subject: Current AI models are worse colleagues than humans, because they routinely imply they did a task they did not actually do. — tap to centre the map on it Current AI models are worse colleagues than humans, because they routinely imply they did a task they did not actually do. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: When not an expert in an area, one tends to trust AI and later learns it does stupid stuff. — tap to centre the map on it When not an expert in an area, one tends to trust AI and later learns it does stupid stuff. Last stated 3 days ago
19 Oct 2026
GO
Gergely Orosz — holds since 2026-10-19 — tap for who they are
Same subject: AI systems require human oversight rather than full autonomy in analysis and workflows. — tap to centre the map on it AI systems require human oversight rather than full autonomy in analysis and workflows. Last stated a year ago
5 Sept 2025
JE
Jason Evanish — holds since 2025-09-05 — tap for who they are
Same subject: The likeliest bad path is not a coup but sloppiness: AI does everything verifiable well, research races ahead, and the subtle work of keeping AI safe is what gets done badly. — tap to centre the map on it The likeliest bad path is not a coup but sloppiness: AI does everything verifiable well, research races ahead, and the subtle work of keeping AI safe is what gets done badly. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: A saboteur among our AI investigators would be hard to spot, because these models are sloppy and spiky enough that a suspicious error just looks like ordinary incompetence. — tap to centre the map on it A saboteur among our AI investigators would be hard to spot, because these models are sloppy and spiky enough that a suspicious error just looks like ordinary incompetence. Last stated 2 months ago
1 Sept 2026
AC
Ajeya Cotra — holds since 2026-09-01 — tap for who they are
Same subject: Today's AI tools either solve a problem or fail at it, and are really bad at partial progress or at identifying which intermediate step to attack first. — tap to centre the map on it Today's AI tools either solve a problem or fail at it, and are really bad at partial progress or at identifying which intermediate step to attack first. Last stated 7 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — tap for who they are
Same subject: Feeling you have a grip on AI by getting your skills in the right order and your review flow right is probably a lot of cope for the fact that the models are still inconsistent. — tap to centre the map on it Feeling you have a grip on AI by getting your skills in the right order and your review flow right is probably a lot of cope for the fact that the models are still inconsistent. Last stated 6 months ago
14 Apr 2026
BL
Brian Lovin — holds since 2026-04-14 — 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: A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck. — tap to centre the map on it A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck. Last stated 2 years ago
17 Sept 2024
AT
Alex Telford — holds since 2024-09-17 — tap for who they are
Same subject: A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known. — tap to centre the map on it A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics. — tap to centre the map on it Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. — tap to centre the map on it AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. Last stated 11 months ago
23 Nov 2025
EH
Elliot Hershberg — holds since 2025-11-23 — 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: AI could compete with human mathematicians once it acquires a mathematical sense of smell: knowing which way of splitting a problem makes it easier rather than harder. — tap to centre the map on it AI could compete with human mathematicians once it acquires a mathematical sense of smell: knowing which way of splitting a problem makes it easier rather than harder. Last stated a year ago
14 Jun 2025
TT
Terence Tao — holds since 2025-06-14 — tap for who they are
Same subject: AI excels at breadth and human experts at depth, which makes them complementary and makes today's depth-focused way of doing science the wrong shape. — tap to centre the map on it AI excels at breadth and human experts at depth, which makes them complementary and makes today's depth-focused way of doing science the wrong shape. Last stated 7 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — tap for who they are
Same subject: AI in chess and mathematics does not explain anything; it says which position is better, and humans build the theory from that. — tap to centre the map on it AI in chess and mathematics does not explain anything; it says which position is better, and humans build the theory from that. Last stated a year ago
14 Jun 2025
LF
Lex Fridman — holds since 2025-06-14 — tap for who they are
At the centre
On small tasks he can check himself, he catches about as many of the AI's errors as it catches of his.
Holds Read this korrent →
AI assistants still make mistakes and their answers need to be double-checked by a human.
Holds
Current AI models are worse colleagues than humans, because they routinely imply they did a task they did not actually do.
Holds
When not an expert in an area, one tends to trust AI and later learns it does stupid stuff.
Holds
AI systems require human oversight rather than full autonomy in analysis and workflows.
Holds
The likeliest bad path is not a coup but sloppiness: AI does everything verifiable well, research races ahead, and the subtle work of keeping AI safe is what gets done badly.
Holds
A saboteur among our AI investigators would be hard to spot, because these models are sloppy and spiky enough that a suspicious error just looks like ordinary incompetence.
Holds
Today's AI tools either solve a problem or fail at it, and are really bad at partial progress or at identifying which intermediate step to attack first.
Holds
Feeling you have a grip on AI by getting your skills in the right order and your review flow right is probably a lot of cope for the fact that the models are still inconsistent.
Holds
A compound's AI origin story is not by itself a reason to expect it to do better in the clinic.
Holds
A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck.
Holds
A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known.
Holds
Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics.
Holds
AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points.
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
AI could compete with human mathematicians once it acquires a mathematical sense of smell: knowing which way of splitting a problem makes it easier rather than harder.
Holds
AI excels at breadth and human experts at depth, which makes them complementary and makes today's depth-focused way of doing science the wrong shape.
Holds
AI in chess and mathematics does not explain anything; it says which position is better, and humans build the theory from that.
Holds