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← Emergent abilities come from generalisation turning compositional, not…
17 connected korrents · 16 moments from 11 Oct 2018 to 26 Aug 2026.
Everything filed under scaling laws
scaling laws
Everything filed under LLMs
LLMs
Everything filed under AGI
AGI
Everything filed under robotics
robotics
Everything filed under mathematics
mathematics
Everything filed under measuring intelligence
measuring intelligence
Everything filed under design
design 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: Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. Last stated a year ago
12 Sept 2025
SL
Sergey Levine — holds since 2025-09-12 — tap for who they are
Same subject: Robot policies already show emergent capability: one transferred a skill from its right hand to its left with no such example anywhere in its training data. — tap to centre the map on it Robot policies already show emergent capability: one transferred a skill from its right hand to its left with no such example anywhere in its training data. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: That people are good at maths and coding, which evolution never selected for, shows human learning is not a complicated evolutionary prior but something more fundamental. — tap to centre the map on it That people are good at maths and coding, which evolution never selected for, shows human learning is not a complicated evolutionary prior but something more fundamental. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: Solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience. — tap to centre the map on it Solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience. Last stated 7 years ago
5 Nov 2019
FC
François Chollet — holds since 2019-11-05 — tap for who they are
Same subject: RL environments exist to make a model generalise, not to teach it each skill one at a time — exactly as pre-training does. — tap to centre the map on it RL environments exist to make a model generalise, not to teach it each skill one at a time — exactly as pre-training does. Last stated 8 months ago
13 Feb 2026
DA
Dario Amodei — holds since 2026-02-13 — tap for who they are
Same subject: Obviousness comes from conforming to people's existing mental models: do not reinvent a common UI pattern unless the new one is at least twice as good. — tap to centre the map on it Obviousness comes from conforming to people's existing mental models: do not reinvent a common UI pattern unless the new one is at least twice as good. Last stated 3 years ago
16 Nov 2023
JZ
Julie Zhuo — holds since 2023-11-16 — tap for who they are
Same subject: Broad deployment of AI that can learn on the job will very likely produce rapid economic growth for some period of time. — tap to centre the map on it Broad deployment of AI that can learn on the job will very likely produce rapid economic growth for some period of time. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: It is the diversity of a robot data set, not its size, that produces generalization: dropping the most diverse slice hurts far more than dropping a random fifth. — tap to centre the map on it It is the diversity of a robot data set, not its size, that produces generalization: dropping the most diverse slice hurts far more than dropping a random fifth. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: If AI can build the new theory that crystallises how to think about a subject, it would be surprising if that capability did not spill into the rest of the economy. — tap to centre the map on it If AI can build the new theory that crystallises how to think about a subject, it would be surprising if that capability did not spill into the rest of the economy. Last stated 4 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: As models keep growing, AI is running out of enough high-quality unique training tokens to keep up. — tap to centre the map on it As models keep growing, AI is running out of enough high-quality unique training tokens to keep up. Last stated 4 months ago
24 Jun 2026
LW
Lilian Weng — holds since 2026-06-24 — tap for who they are
Same subject: Current techniques restrict pre-trained representation power because standard language models are unidirectional. — tap to centre the map on it Current techniques restrict pre-trained representation power because standard language models are unidirectional. 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: If reasoning can be separated from facts, the frontier labs lose their advantage, because nobody needs a million-GPU cluster any more. — tap to centre the map on it If reasoning can be separated from facts, the frontier labs lose their advantage, because nobody needs a million-GPU cluster any more. Last stated 2 years ago
19 Jun 2024
AS
Aravind Srinivas — holds since 2024-06-19 — tap for who they are
Same subject: Language models perform better on benchmark problems released before their training data cutoff, indicating data contamination inflates scores. — tap to centre the map on it Language models perform better on benchmark problems released before their training data cutoff, indicating data contamination inflates scores. Last stated 2 years ago
13 May 2024
SR
Sebastian Ruder — holds since 2024-05-13 — tap for who they are
Same subject: Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared. — tap to centre the map on it Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared. Last stated 2 months ago
26 Aug 2026
DH
David Heinemeier Hansson — holds since 2026-08-26 — tap for who they are
Same subject: Local AI models will eventually catch up to frontier models once frontier progress hits diminishing returns. — tap to centre the map on it Local AI models will eventually catch up to frontier models once frontier progress hits diminishing returns. Last stated 8 months ago
8 Feb 2026
DC
David Crawshaw — holds since 2026-02-08 — tap for who they are
Same subject: A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact. — tap to centre the map on it A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact. Last stated 8 months ago
12 Feb 2026
AK
Andrej Karpathy — holds since 2026-02-12 — tap for who they are
Same subject: AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun. — tap to centre the map on it AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected. — tap to centre the map on it An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected. Last stated 4 years ago
21 Mar 2023
BC
Bryan Caplan — holds since 2023-03-21 — tap for who they are
At the centre
Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff.
Holds Read this korrent →
Robot policies already show emergent capability: one transferred a skill from its right hand to its left with no such example anywhere in its training data.
Holds
That people are good at maths and coding, which evolution never selected for, shows human learning is not a complicated evolutionary prior but something more fundamental.
Holds
Solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience.
Holds
RL environments exist to make a model generalise, not to teach it each skill one at a time — exactly as pre-training does.
Holds
Obviousness comes from conforming to people's existing mental models: do not reinvent a common UI pattern unless the new one is at least twice as good.
Holds
Broad deployment of AI that can learn on the job will very likely produce rapid economic growth for some period of time.
Holds
It is the diversity of a robot data set, not its size, that produces generalization: dropping the most diverse slice hurts far more than dropping a random fifth.
Holds
If AI can build the new theory that crystallises how to think about a subject, it would be surprising if that capability did not spill into the rest of the economy.
Holds
As models keep growing, AI is running out of enough high-quality unique training tokens to keep up.
Holds
Current techniques restrict pre-trained representation power because standard language models are unidirectional.
Holds
If reasoning can be separated from facts, the frontier labs lose their advantage, because nobody needs a million-GPU cluster any more.
Holds
Language models perform better on benchmark problems released before their training data cutoff, indicating data contamination inflates scores.
Holds
Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared.
Holds
Local AI models will eventually catch up to frontier models once frontier progress hits diminishing returns.
Holds
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.
Holds
AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun.
Holds
An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected.
Holds