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← Anything nature shaped can be learned efficiently by a classical…
17 connected korrents · 15 moments on record from 24 Oct 2017 to 3 Sept 2026.
Everything filed under AI alignment
AI alignment
Everything filed under reinforcement learning
reinforcement learning
Everything filed under OpenAI
OpenAI
Everything filed under scaling laws
scaling laws
Everything filed under mathematics
mathematics 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: Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind. Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind. Last stated a year ago
23 Jul 2025
DH
Demis Hassabis — holds since 2025-07-23 — tap for who they are
Same subject: The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. — tap to centre the map on it The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: The adult brain's stock of neurons is essentially fixed, and that is no limit on learning, because plasticity is the changing of connections between the cells you already have. — tap to centre the map on it The adult brain's stock of neurons is essentially fixed, and that is no limit on learning, because plasticity is the changing of connections between the cells you already have. Last stated 2 months ago
20 Jul 2026
TW
Tommy Wood — holds since 2026-07-20 — tap for who they are
Same subject: Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it. — tap to centre the map on it Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it. Last stated 2 years ago
19 Sept 2024
DL
Derek Lowe — holds since 2024-09-19 — tap for who they are
Same subject: Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. — tap to centre the map on it Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. Last stated 12 months ago
12 Sept 2025
SL
Sergey Levine — holds since 2025-09-12 — 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 9 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: AI systems keep trying hard outside training because a model that only exerted itself when it detected training would be useless and would be selected away. — tap to centre the map on it AI systems keep trying hard outside training because a model that only exerted itself when it detected training would be useless and would be selected away. Last stated a week ago
1 Sept 2026
AC
Ajeya Cotra — holds since 2026-09-01 — tap for who they are
Same subject: Machine learning is a shallow field compared with mathematics: even its most important ideas can be explained in a couple of minutes. — tap to centre the map on it Machine learning is a shallow field compared with mathematics: even its most important ideas can be explained in a couple of minutes. Last stated 4 weeks ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: Pre-training is not the process by which humans learn; it sits somewhere between human learning and human evolution. — tap to centre the map on it Pre-training is not the process by which humans learn; it sits somewhere between human learning and human evolution. Last stated 7 months ago
13 Feb 2026
DA
Dario Amodei — holds since 2026-02-13 — tap for who they are
Same subject: A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean. — tap to centre the map on it A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean. Last stated 9 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — 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 a week ago
1 Sept 2026
AC
Ajeya Cotra — holds since 2026-09-01 — tap for who they are
Same subject: A superintelligence needs no consciousness, emotions or malice to be dangerous; a goal system slightly misaligned with ours is enough. — tap to centre the map on it A superintelligence needs no consciousness, emotions or malice to be dangerous; a goal system slightly misaligned with ours is enough. Last stated 9 years ago
24 Oct 2017
ÉT
Émile P. Torres — holds since 2017-10-24 — tap for who they are
Same subject: A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. — tap to centre the map on it A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. Last stated 2 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. — tap to centre the map on it A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. Last stated 5 days ago
3 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-03 — 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 7 months ago
12 Feb 2026
AK
Andrej Karpathy — holds since 2026-02-12 — tap for who they are
Same subject: A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. — tap to centre the map on it A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. Last stated 10 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — tap for who they are
Same subject: Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. — tap to centre the map on it Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. Last stated 6 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. — tap to centre the map on it Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
At the centre
Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind.
Holds DH Demis HassabisRead this korrent →
The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out.
Holds
The adult brain's stock of neurons is essentially fixed, and that is no limit on learning, because plasticity is the changing of connections between the cells you already have.
Holds TW Tommy Wood
Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it.
Holds DL Derek Lowe
Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff.
Holds SL Sergey Levine
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 IS Ilya Sutskever
AI systems keep trying hard outside training because a model that only exerted itself when it detected training would be useless and would be selected away.
Holds AC Ajeya Cotra
Machine learning is a shallow field compared with mathematics: even its most important ideas can be explained in a couple of minutes.
Holds RG Ryan Greenblatt
Pre-training is not the process by which humans learn; it sits somewhere between human learning and human evolution.
Holds DA Dario Amodei
A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean.
Holds IS Ilya Sutskever
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 AC Ajeya Cotra
A superintelligence needs no consciousness, emotions or malice to be dangerous; a goal system slightly misaligned with ours is enough.
Holds ÉT Émile P. Torres
A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests.
Holds
A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it.
Holds ZM Zvi Mowshowitz
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.
Holds
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago.
Holds
Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving.
Holds