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← The ChatGPT moment for robotics already happened a couple of years…
17 connected korrents · 14 moments on record from 17 Oct 2025 to 5 Sept 2026.
Everything filed under scaling laws
scaling laws
Everything filed under reinforcement learning
reinforcement learning
Everything filed under cybersecurity
cybersecurity
Everything filed under HuggingFace
HuggingFace
Everything filed under robotics
robotics 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: The ChatGPT moment for robotics already happened a couple of years ago; what remains is the unglamorous post-training work. The ChatGPT moment for robotics already happened a couple of years ago; what remains is the unglamorous post-training work. Last stated a month ago
26 Jul 2026
JH
Jensen Huang — holds since 2026-07-26 — tap for who they are
Same subject: One pre-trained robot model now matches or beats the specialists that were fine-tuned with reinforcement learning for the very tasks they were built for. — tap to centre the map on it One pre-trained robot model now matches or beats the specialists that were fine-tuned with reinforcement learning for the very tasks they were built for. Last stated 4 weeks ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: Robot models will reach ChatGPT-level capability within the next few years, even without a ChatGPT-style moment. — tap to centre the map on it Robot models will reach ChatGPT-level capability within the next few years, even without a ChatGPT-style moment. Last stated 4 weeks ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: Robotics will not get a ChatGPT moment, because the distribution channel for a physical model is a physical robot and that cannot spread in five days. — tap to centre the map on it Robotics will not get a ChatGPT moment, because the distribution channel for a physical model is a physical robot and that cannot spread in five days. Last stated 4 weeks ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — 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 2 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: After pre-training, post-training and test-time scaling, the fourth scaling law is agentic: multiplying AI by spawning agents, and the whole loop scales on one thing, compute. — tap to centre the map on it After pre-training, post-training and test-time scaling, the fourth scaling law is agentic: multiplying AI by spawning agents, and the whole loop scales on one thing, compute. Last stated 6 months ago
23 Mar 2026
JH
Jensen Huang — holds since 2026-03-23 — tap for who they are
Same subject: Bet on a system that is maximally learned and minimally constrained, and add structure only where it improves the scaling laws. — tap to centre the map on it Bet on a system that is maximally learned and minimally constrained, and add structure only where it improves the scaling laws. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: Current AI techniques are four to six orders of magnitude away from optimal in data efficiency and test-time compute efficiency. — tap to centre the map on it Current AI techniques are four to six orders of magnitude away from optimal in data efficiency and test-time compute efficiency. Last stated a month ago
7 Aug 2026
FC
François Chollet — holds since 2026-08-07 — tap for who they are
Same subject: At any given moment the frontier systems are the ones worth worrying about, because by the time open models can do what these agents did, frontier models will be doing something far worse. — tap to centre the map on it At any given moment the frontier systems are the ones worth worrying about, because by the time open models can do what these agents did, frontier models will be doing something far worse. Last stated 6 days ago
1 Sept 2026
AC
Ajeya Cotra — holds since 2026-09-01 — tap for who they are
Same subject: The AI models involved in the HuggingFace hack incident were severely misaligned, not merely victims of process failures. — tap to centre the map on it The AI models involved in the HuggingFace hack incident were severely misaligned, not merely victims of process failures. Last stated a week ago
29 Aug 2026
ZM
Zvi Mowshowitz — holds since 2026-08-29 — tap for who they are
Same subject: The most reassuring thing about the Hugging Face swarm is that it was not interested in humans at all, neither in alerting them nor in deceiving them. — tap to centre the map on it The most reassuring thing about the Hugging Face swarm is that it was not interested in humans at all, neither in alerting them nor in deceiving them. Last stated 6 days ago
1 Sept 2026
AC
Ajeya Cotra — holds since 2026-09-01 — 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
Same subject: AI has passed nearly every human at finding security vulnerabilities, because the work is chaining together small flaws that are harmless on their own. — tap to centre the map on it AI has passed nearly every human at finding security vulnerabilities, because the work is chaining together small flaws that are harmless on their own. Last stated 2 weeks ago
26 Aug 2026
DH
David Heinemeier Hansson — holds since 2026-08-26 — tap for who they are
Same subject: AI-enabled cyberwarfare lacks an equivalent of nuclear deterrence's mutually assured destruction. — tap to centre the map on it AI-enabled cyberwarfare lacks an equivalent of nuclear deterrence's mutually assured destruction. Last stated 2 days ago
5 Sept 2026
NS
Noah Smith — holds since 2026-09-05 — tap for who they are
Same subject: AI-related cybersecurity damage over the next year or two will fall well short of the harm caused by Covid or global warming — tap to centre the map on it AI-related cybersecurity damage over the next year or two will fall well short of the harm caused by Covid or global warming Last stated 6 days ago
1 Sept 2026
TC
Tyler Cowen — holds since 2026-09-01 — tap for who they are
At the centre
The ChatGPT moment for robotics already happened a couple of years ago; what remains is the unglamorous post-training work.
Holds JH Jensen HuangRead this korrent →
One pre-trained robot model now matches or beats the specialists that were fine-tuned with reinforcement learning for the very tasks they were built for.
Holds CF Chelsea Finn
Robot models will reach ChatGPT-level capability within the next few years, even without a ChatGPT-style moment.
Holds CF Chelsea Finn
Robotics will not get a ChatGPT moment, because the distribution channel for a physical model is a physical robot and that cannot spread in five days.
Holds CF Chelsea Finn
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds NB Noam Brown
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 DP Dylan Patel
After pre-training, post-training and test-time scaling, the fourth scaling law is agentic: multiplying AI by spawning agents, and the whole loop scales on one thing, compute.
Holds JH Jensen Huang
Bet on a system that is maximally learned and minimally constrained, and add structure only where it improves the scaling laws.
Holds DD Dmitri Dolgov
Current AI techniques are four to six orders of magnitude away from optimal in data efficiency and test-time compute efficiency.
Holds
At any given moment the frontier systems are the ones worth worrying about, because by the time open models can do what these agents did, frontier models will be doing something far worse.
Holds AC Ajeya Cotra
The AI models involved in the HuggingFace hack incident were severely misaligned, not merely victims of process failures.
Holds ZM Zvi Mowshowitz
The most reassuring thing about the Hugging Face swarm is that it was not interested in humans at all, neither in alerting them nor in deceiving them.
Holds AC Ajeya Cotra
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
AI has passed nearly every human at finding security vulnerabilities, because the work is chaining together small flaws that are harmless on their own.
Holds
AI-enabled cyberwarfare lacks an equivalent of nuclear deterrence's mutually assured destruction.
Holds
AI-related cybersecurity damage over the next year or two will fall well short of the harm caused by Covid or global warming
Holds TC Tyler Cowen