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← Humans can generally perform new language tasks from few examples or…
17 connected korrents · 13 moments on record from 11 Oct 2018 to 11 Aug 2026.
Everything filed under LLMs
LLMs
Everything filed under robotics
robotics
Everything filed under reinforcement learning
reinforcement learning
Everything filed under measuring intelligence
measuring intelligence
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: Humans can generally perform new language tasks from few examples or simple instructions, while current NLP systems largely cannot. Humans can generally perform new language tasks from few examples or simple instructions, while current NLP systems largely cannot. Last stated 6 years ago
28 May 2020
DA
Dario Amodei — holds since 2020-05-28 — tap for who they are
Same subject: Once a robot is good enough, you can teach it with words instead of with demonstrations, and language becomes a training signal for motor skill. — tap to centre the map on it Once a robot is good enough, you can teach it with words instead of with demonstrations, and language becomes a training signal for motor skill. Last stated 12 months ago
12 Sept 2025
SL
Sergey Levine — holds since 2025-09-12 — tap for who they are
Same subject: Large language models mimic what people say to do rather than work out what to do, which is why they are not about understanding the world. — tap to centre the map on it Large language models mimic what people say to do rather than work out what to do, which is why they are not about understanding the world. Last stated 11 months ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own. — tap to centre the map on it Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: Letting more people write software in natural language does not reduce the work; it snowballs the amount of software that has to be maintained. — tap to centre the map on it Letting more people write software in natural language does not reduce the work; it snowballs the amount of software that has to be maintained. Last stated a year ago
22 Mar 2025
TH
ThePrimeagen — holds since 2025-03-22 — tap for who they are
Same subject: There is essentially no cognitive task humans do where AI improvement is failing to transfer at all. — tap to centre the map on it There is essentially no cognitive task humans do where AI improvement is failing to transfer at all. Last stated 4 weeks ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — 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 11 months ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — 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: Computer-use agents had to wait for language models: without pre-trained representations the reward is too sparse to ever learn from. — tap to centre the map on it Computer-use agents had to wait for language models: without pre-trained representations the reward is too sparse to ever learn from. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas. — tap to centre the map on it A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas. Last stated 3 years ago
1 Oct 2023
TC
Tyler Cowen — holds since 2023-10-01 — tap for who they are
Same subject: A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it. — tap to centre the map on it A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it. Last stated a year ago
6 Apr 2025
MH
Molson Hart — holds since 2025-04-06 — tap for who they are
Same subject: A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. — tap to centre the map on it A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: If intelligence is the process of acquiring skills, no single task demonstrates intelligence unless it is a meta-task of skill-acquisition across many tasks. — tap to centre the map on it If intelligence is the process of acquiring skills, no single task demonstrates intelligence unless it is a meta-task of skill-acquisition across many tasks. Last stated 7 years ago
5 Nov 2019
FC
François Chollet — holds since 2019-11-05 — 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: The Abstraction and Reasoning Corpus can measure human-like general fluid intelligence and enable fair comparisons between AI systems and humans. — tap to centre the map on it The Abstraction and Reasoning Corpus can measure human-like general fluid intelligence and enable fair comparisons between AI systems and humans. Last stated 7 years ago
5 Nov 2019
FC
François Chollet — holds since 2019-11-05 — tap for who they are
Same subject: A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. — tap to centre the map on it A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — 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: Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model. — tap to centre the map on it Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
At the centre
Humans can generally perform new language tasks from few examples or simple instructions, while current NLP systems largely cannot.
Holds DA Dario AmodeiRead this korrent →
Once a robot is good enough, you can teach it with words instead of with demonstrations, and language becomes a training signal for motor skill.
Holds SL Sergey Levine
Large language models mimic what people say to do rather than work out what to do, which is why they are not about understanding the world.
Holds RS Richard Sutton
Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own.
Holds NL Nathan Lambert
Letting more people write software in natural language does not reduce the work; it snowballs the amount of software that has to be maintained.
Holds TH ThePrimeagen
There is essentially no cognitive task humans do where AI improvement is failing to transfer at all.
Holds RG Ryan Greenblatt
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 RS Richard Sutton
Current techniques restrict pre-trained representation power because standard language models are unidirectional.
Holds KT Kristina ToutanovaMC Ming-Wei ChangKL Kenton LeeJD Jacob Devlin
Computer-use agents had to wait for language models: without pre-trained representations the reward is too sparse to ever learn from.
Holds
A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas.
Holds TC Tyler Cowen
A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it.
Holds MH Molson Hart
A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases.
Holds DD Dmitri Dolgov
If intelligence is the process of acquiring skills, no single task demonstrates intelligence unless it is a meta-task of skill-acquisition across many tasks.
Holds
Solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience.
Holds
The Abstraction and Reasoning Corpus can measure human-like general fluid intelligence and enable fair comparisons between AI systems and humans.
Holds
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Holds DD Dmitri Dolgov
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model.
Holds DD Dmitri Dolgov