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← Real-world physical tasks cannot be solved through autoregressive sampling alone.
17 connected korrents · 14 moments from 18 Mar 2024 to 14 Oct 2026.
Everything filed under robotics
robotics
Everything filed under scaling laws
scaling laws
Everything filed under Anthropic
Anthropic
Everything filed under OpenAI
OpenAI
Everything filed under physics
physics
Everything filed under LLMs
LLMs
Everything filed under AI alignment
AI alignment 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: Real-world physical tasks cannot be solved through autoregressive sampling alone. Real-world physical tasks cannot be solved through autoregressive sampling alone. Last stated yesterday
14 Oct 2026
FC
François Chollet — holds since 2026-10-14 — tap for who they are
Same subject: AI is not yet capable of autonomously handling all real-world tasks. — tap to centre the map on it AI is not yet capable of autonomously handling all real-world tasks. Last stated 3 weeks ago
23 Sept 2026
MS
M.G. Siegler — holds since 2026-09-23 — tap for who they are
Same subject: Current AI struggles even to rediscover old laws of physics from data, and when it does, contamination from training is the first suspect. — tap to centre the map on it Current AI struggles even to rediscover old laws of physics from data, and when it does, contamination from training is the first suspect. Last stated a year ago
14 Jun 2025
TT
Terence Tao — holds since 2025-06-14 — tap for who they are
Same subject: AI will not run out of data, because there is already enough real-world data to build the simulators that generate more of it. — tap to centre the map on it AI will not run out of data, because there is already enough real-world data to build the simulators that generate more of it. Last stated a year ago
23 Jul 2025
DH
Demis Hassabis — holds since 2025-07-23 — tap for who they are
Same subject: AI cannot get a product to the quality bar on its own, because it still works in the realm of averages. — tap to centre the map on it AI cannot get a product to the quality bar on its own, because it still works in the realm of averages. Last stated 12 months ago
16 Oct 2025
DF
Dylan Field — holds since 2025-10-16 — tap for who they are
Same subject: Letting a robot imagine the next image helps, but it is not essential — the model was surprisingly good without it. — tap to centre the map on it Letting a robot imagine the next image helps, but it is not essential — the model was surprisingly good without it. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: Confidence in monitoring, not capability research, will become the binding constraint on AI progress. — tap to centre the map on it Confidence in monitoring, not capability research, will become the binding constraint on AI progress. Last stated a month ago
6 Sept 2026
JP
Jakub Pachocki — holds since 2026-09-06 — tap for who they are
Same subject: Hand-tuning a robot's data set cannot reach very high reliability, because people get tired; the system has to seek out its own missing data. — tap to centre the map on it Hand-tuning a robot's data set cannot reach very high reliability, because people get tired; the system has to seek out its own missing data. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute. — tap to centre the map on it Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — 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 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. — tap to centre the map on it Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: Agents are going to be incorporated into mainstream interfaces — tap to centre the map on it Agents are going to be incorporated into mainstream interfaces Last stated 7 months ago
25 Mar 2026
DH
David Heinemeier Hansson — holds since 2026-03-25 — 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: "I don't know" becomes a kind of superpower when you can work with Claude Code to figure things out. — tap to centre the map on it "I don't know" becomes a kind of superpower when you can work with Claude Code to figure things out. Last stated 7 months ago
19 Mar 2026
KP
Kris Puckett — holds since 2026-03-19 — tap for who they are
Same subject: A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. — tap to centre the map on it A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. Last stated a month ago
3 Sept 2026
DR
Dax Raad — holds since 2026-09-03 — tap for who they are
Same subject: A skill is a set of repeatable, specific instructions that augments what Claude Code can do. — tap to centre the map on it A skill is a set of repeatable, specific instructions that augments what Claude Code can do. Last stated 7 months ago
19 Mar 2026
KP
Kris Puckett — holds since 2026-03-19 — tap for who they are
At the centre
Real-world physical tasks cannot be solved through autoregressive sampling alone.
Holds Read this korrent →
AI is not yet capable of autonomously handling all real-world tasks.
Holds
Current AI struggles even to rediscover old laws of physics from data, and when it does, contamination from training is the first suspect.
Holds
AI will not run out of data, because there is already enough real-world data to build the simulators that generate more of it.
Holds
AI cannot get a product to the quality bar on its own, because it still works in the realm of averages.
Holds
Letting a robot imagine the next image helps, but it is not essential — the model was surprisingly good without it.
Holds
Confidence in monitoring, not capability research, will become the binding constraint on AI progress.
Holds
Hand-tuning a robot's data set cannot reach very high reliability, because people get tired; the system has to seek out its own missing data.
Holds
Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute.
Holds
A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests.
Holds
Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers.
Holds
Agents are going to be incorporated into mainstream interfaces
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
"I don't know" becomes a kind of superpower when you can work with Claude Code to figure things out.
Holds
A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year.
Holds
A skill is a set of repeatable, specific instructions that augments what Claude Code can do.
Holds