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← Frontier language models will remain reasoning models trained with…
17 connected korrents · 18 moments on record from 5 Nov 2019 to 18 Sept 2026.
Everything filed under LLMs
LLMs
Everything filed under AI writing
AI writing
Everything filed under measuring intelligence
measuring intelligence
Everything filed under scaling laws
scaling laws 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: Frontier language models will remain reasoning models trained with RLVR-style chain-of-thought for the foreseeable future. Frontier language models will remain reasoning models trained with RLVR-style chain-of-thought for the foreseeable future. Last stated 2 weeks ago
9 Sept 2026
SR
Sebastian Raschka — holds since 2026-09-09 — tap for who they are
Same subject: A computer scientist refusing to find LLMs interesting is like a geneticist ignoring Jurassic Park. — tap to centre the map on it A computer scientist refusing to find LLMs interesting is like a geneticist ignoring Jurassic Park. Last stated 3 days ago
18 Sept 2026
SW
Simon Willison — holds since 2026-09-18 — tap for who they are
Same subject: A language model asked to summarize its own system prompt risks that prompt's content biasing the summary it produces. — tap to centre the map on it A language model asked to summarize its own system prompt risks that prompt's content biasing the summary it produces. Last stated 3 weeks ago
2 Sept 2026
SW
Simon Willison — holds since 2026-09-02 — tap for who they are
Same subject: A language model avoids hallucinating only by being factual and admitting when it does not know the answer. — tap to centre the map on it A language model avoids hallucinating only by being factual and admitting when it does not know the answer. Last stated 2 years ago
7 Jul 2024
LW
Lilian Weng — holds since 2024-07-07 — tap for who they are
Same subject: A language model can predict what a person would say but not what will happen, and only the second of those is a model of the world. — tap to centre the map on it A language model can predict what a person would say but not what will happen, and only the second of those is a model of the world. Last stated 12 months ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: A language model cannot produce work that is both original and good, because nothing gives it a score for originality. — tap to centre the map on it A language model cannot produce work that is both original and good, because nothing gives it a score for originality. Last stated a year ago
2 Sept 2025
BE
Benedict Evans — holds since 2025-09-02 — tap for who they are
Same subject: A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. — tap to centre the map on it A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. Last stated a year ago
7 Jun 2025
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: A language model is not using language at all, because language requires an intention to communicate. — tap to centre the map on it A language model is not using language at all, because language requires an intention to communicate. Last stated 2 years ago
31 Aug 2024
TC
Ted Chiang — holds since 2024-08-31 — tap for who they are
Same subject: A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human. — tap to centre the map on it A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human. Last stated 2 years ago
22 Apr 2024
SC
Sean Carroll — holds since 2024-04-22 — tap for who they are
Same subject: A true artificial general intelligence cannot exist without being recognized as a moral subject. — tap to centre the map on it A true artificial general intelligence cannot exist without being recognized as a moral subject. Last stated a year ago
10 Jun 2025
SH
Samuel Hammond — holds since 2025-06-10 — tap for who they are
Same subject: A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model. — tap to centre the map on it A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model. Last stated 6 days ago
15 Sept 2026
PG
Paul Graham — holds since 2026-09-15 — tap for who they are
Same subject: Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect. — tap to centre the map on it Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect. Last stated 7 years ago
5 Nov 2019
FC
François Chollet — holds since 2019-11-05 — tap for who they are
Same subject: "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. — tap to centre the map on it "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. Last stated 10 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. — tap to centre the map on it A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. Last stated 3 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. — tap to centre the map on it A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. Last stated 6 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — 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: AI content should be labelled rather than filtered: content should be judged by its point of view, never by the tool that made it. — tap to centre the map on it AI content should be labelled rather than filtered: content should be judged by its point of view, never by the tool that made it. Last stated 2 months ago
9 Jul 2026
AM
Adam Mosseri — holds since 2026-07-09 — tap for who they are
Same subject: AI writing tools can be used for editing help without letting them take over work that has personal meaning. — tap to centre the map on it AI writing tools can be used for editing help without letting them take over work that has personal meaning. Last stated 2 months ago
27 Jul 2026
AH
Ann Handley — holds since 2026-07-27 — tap for who they are
At the centre
Frontier language models will remain reasoning models trained with RLVR-style chain-of-thought for the foreseeable future.
Holds Read this korrent →
A computer scientist refusing to find LLMs interesting is like a geneticist ignoring Jurassic Park.
Holds
A language model asked to summarize its own system prompt risks that prompt's content biasing the summary it produces.
Holds
A language model avoids hallucinating only by being factual and admitting when it does not know the answer.
Holds
A language model can predict what a person would say but not what will happen, and only the second of those is a model of the world.
Holds
A language model cannot produce work that is both original and good, because nothing gives it a score for originality.
Holds
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
Holds
A language model is not using language at all, because language requires an intention to communicate.
Holds
A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human.
Holds
A true artificial general intelligence cannot exist without being recognized as a moral subject.
Holds
A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model.
Holds
Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect.
Holds
"Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next.
Holds
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds
A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from.
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
AI content should be labelled rather than filtered: content should be judged by its point of view, never by the tool that made it.
Holds
AI writing tools can be used for editing help without letting them take over work that has personal meaning.
Holds