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← Language models are already a form of AGI; what the labs are chasing…
17 connected korrents · 18 moments from 3 Oct 2012 to 27 Sept 2026.
Everything filed under measuring intelligence
measuring intelligence
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scaling laws
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AI alignment
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AI writing
Everything filed under AGI
AGI 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: Language models are already a form of AGI; what the labs are chasing is a further step, not the arrival of general intelligence. Language models are already a form of AGI; what the labs are chasing is a further step, not the arrival of general intelligence. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read. — tap to centre the map on it Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read. Last stated a year ago
30 Jul 2025
AG
Alexey Guzey — holds since 2024-08-09 — tap for who they are
AG
Alexey Guzey — no longer holds since 2025-07-30 — 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: AGI research made no progress in its first six decades. — tap to centre the map on it AGI research made no progress in its first six decades. Last stated 14 years ago
3 Oct 2012
DD
David Deutsch — holds since 2012-10-03 — tap for who they are
Same subject: The LLM line of research will reach a capability plateau. — tap to centre the map on it The LLM line of research will reach a capability plateau. Last stated 3 months ago
7 Aug 2026
FC
François Chollet — no longer holds since 2026-08-07 — tap for who they are
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: The memorize-fetch-apply paradigm behind LLMs can reach arbitrary skill given training data, but it cannot adapt to novelty or acquire new skills on the fly. — tap to centre the map on it The memorize-fetch-apply paradigm behind LLMs can reach arbitrary skill given training data, but it cannot adapt to novelty or acquire new skills on the fly. Last stated 2 years ago
20 Dec 2024
FC
François Chollet — holds since 2024-12-20 — tap for who they are
FC
François Chollet — no longer holds since 2024-12-20 — 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: Anyone who thinks large language models are a direct route to transformative AGI is kidding themselves. — tap to centre the map on it Anyone who thinks large language models are a direct route to transformative AGI is kidding themselves. Last stated a year ago
7 Jun 2025
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: General intelligence (g) reflects an overall pool of neural resources rooted in whole-body developmental integrity, making it a large mutational target rather than a distinct cognitive module. — tap to centre the map on it General intelligence (g) reflects an overall pool of neural resources rooted in whole-body developmental integrity, making it a large mutational target rather than a distinct cognitive module. Last stated 5 years ago
11 Jun 2021
GW
Gwern — holds since 2021-06-11 — tap for who they are
Same subject: A company that uses an algorithm to nudge customers into behavior that isn't good for them is doing something bad. — tap to centre the map on it A company that uses an algorithm to nudge customers into behavior that isn't good for them is doing something bad. Last stated a year ago
7 Oct 2025
MM
Mr. Money Mustache — holds since 2025-10-07 — 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 feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score. — tap to centre the map on it A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score. Last stated 2 months ago
26 Aug 2026
HK
Henrik Karlsson — holds since 2026-08-26 — 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 11 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 4 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 7 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: A CEO who sends out an AI-written strategy memo is modelling that it is fine to outsource thinking and strategy. — tap to centre the map on it A CEO who sends out an AI-written strategy memo is modelling that it is fine to outsource thinking and strategy. Last stated 4 weeks ago
27 Sept 2026
MG
Molly Graham — holds since 2026-09-27 — 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: AI can now produce in minutes work that used to take weeks to build. — tap to centre the map on it AI can now produce in minutes work that used to take weeks to build. Last stated 5 months ago
26 May 2026
CB
Carlos Alexandro Becker — holds since 2026-05-26 — tap for who they are
At the centre
Language models are already a form of AGI; what the labs are chasing is a further step, not the arrival of general intelligence.
Holds Read this korrent →
Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read.
No longer holds
A true artificial general intelligence cannot exist without being recognized as a moral subject.
Holds
AGI research made no progress in its first six decades.
Holds
The LLM line of research will reach a capability plateau.
Holds No longer holds
The memorize-fetch-apply paradigm behind LLMs can reach arbitrary skill given training data, but it cannot adapt to novelty or acquire new skills on the fly.
No longer 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
Anyone who thinks large language models are a direct route to transformative AGI is kidding themselves.
Holds
General intelligence (g) reflects an overall pool of neural resources rooted in whole-body developmental integrity, making it a large mutational target rather than a distinct cognitive module.
Holds
A company that uses an algorithm to nudge customers into behavior that isn't good for them is doing something bad.
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 feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score.
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 CEO who sends out an AI-written strategy memo is modelling that it is fine to outsource thinking and strategy.
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 can now produce in minutes work that used to take weeks to build.
Holds