Tap a claim on the ring to put it at the centre.
← Language models supply robots with the one thing self-driving never…
17 connected korrents · 18 moments on record from 22 Apr 2024 to 14 May 2026. Nearly all of them are about self-driving cars .
Everything filed under robotics
robotics
Everything filed under LLMs
LLMs
Everything filed under reinforcement learning
reinforcement learning 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: Language models supply robots with the one thing self-driving never had: common sense about what is likely to happen next. Language models supply robots with the one thing self-driving never had: common sense about what is likely to happen next. Last stated 12 months ago
12 Sept 2025
SL
Sergey Levine — holds since 2025-09-12 — tap for who they are
Same subject: A world of a billion robots will need maintenance crews and hubs the way robotaxis already do, creating the largest repair industry on the planet. — tap to centre the map on it A world of a billion robots will need maintenance crews and hubs the way robotaxis already do, creating the largest repair industry on the planet. Last stated 8 months ago
8 Jan 2026
JH
Jensen Huang — holds since 2026-01-08 — tap for who they are
Same subject: Robotics is not easier than self-driving; it is simply being attempted in a year when perception actually generalises. — tap to centre the map on it Robotics is not easier than self-driving; it is simply being attempted in a year when perception actually generalises. 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 will not get to real agency, because a mind has to be embedded in a world through a body. — tap to centre the map on it Large language models will not get to real agency, because a mind has to be embedded in a world through a body. Last stated 2 years ago
22 Dec 2024
AF
Adam Frank — holds since 2024-12-22 — tap for who they are
Same subject: A five-year-old's vision is already good enough to drive a car, on a tiny and strikingly undiverse amount of data. — tap to centre the map on it A five-year-old's vision is already good enough to drive a car, on a tiny and strikingly undiverse amount of data. Last stated 9 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A good robotaxi demonstration in one city does not mean the company is ready to scale the service. — tap to centre the map on it A good robotaxi demonstration in one city does not mean the company is ready to scale the service. Last stated a year ago
8 Jul 2025
TL
Timothy B. Lee — holds since 2025-07-08 — tap for who they are
Same subject: A huge fleet collecting driving data is not a silver bullet for self-driving, because the data arrives unlabelled. — tap to centre the map on it A huge fleet collecting driving data is not a silver bullet for self-driving, because the data arrives unlabelled. Last stated 2 years ago
21 May 2024
TL
Timothy B. Lee — holds since 2024-05-21 — tap for who they are
Same subject: A large majority of the serious crashes a robotaxi is involved in are caused by the other road user, not by the robotaxi. — tap to centre the map on it A large majority of the serious crashes a robotaxi is involved in are caused by the other road user, not by the robotaxi. Last stated a year ago
26 Mar 2025
TL
Timothy B. Lee — holds since 2025-03-26 — tap for who they are
Same subject: A privately owned self-driving car is a hard sell, because the owner inherits the cleaning, calibration and liability a fleet operator normally carries. — tap to centre the map on it A privately owned self-driving car is a hard sell, because the owner inherits the cleaning, calibration and liability a fleet operator normally carries. Last stated 4 months ago
14 May 2026
TL
Timothy B. Lee — holds since 2026-05-14 — tap for who they are
Same subject: A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. — tap to centre the map on it A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. Last stated a year ago
7 Jun 2025
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: A language model is not using language at all, because language requires an intention to communicate. — tap to centre the map on it A language model is not using language at all, because language requires an intention to communicate. Last stated 2 years ago
31 Aug 2024
TC
Ted Chiang — holds since 2024-08-31 — tap for who they are
Same subject: A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human. — tap to centre the map on it A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human. Last stated 2 years ago
22 Apr 2024
SC
Sean Carroll — holds since 2024-04-22 — 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: Process supervision by an LLM judge cannot be run for long, because a judge with billions of parameters is gameable and RL will find its cracks. — tap to centre the map on it Process supervision by an LLM judge cannot be run for long, because a judge with billions of parameters is gameable and RL will find its cracks. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — 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: 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: The memorize-fetch-apply paradigm behind LLMs can reach arbitrary skill given training data, but it cannot adapt to novelty or acquire new skills on the fly. — tap to centre the map on it The memorize-fetch-apply paradigm behind LLMs can reach arbitrary skill given training data, but it cannot adapt to novelty or acquire new skills on the fly. Last stated 2 years ago
20 Dec 2024
FC
François Chollet — holds since 2024-12-20 — tap for who they are
FC
François Chollet — no longer holds since 2024-12-20 — tap for who they are
Same subject: Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read. — tap to centre the map on it Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read. Last stated a year ago
30 Jul 2025
AG
Alexey Guzey — holds since 2024-08-09 — tap for who they are
AG
Alexey Guzey — no longer holds since 2025-07-30 — tap for who they are
At the centre
Language models supply robots with the one thing self-driving never had: common sense about what is likely to happen next.
Holds SL Sergey LevineRead this korrent →
A world of a billion robots will need maintenance crews and hubs the way robotaxis already do, creating the largest repair industry on the planet.
Holds JH Jensen Huang
Robotics is not easier than self-driving; it is simply being attempted in a year when perception actually generalises.
Holds SL Sergey Levine
Large language models will not get to real agency, because a mind has to be embedded in a world through a body.
Holds AF Adam Frank
A five-year-old's vision is already good enough to drive a car, on a tiny and strikingly undiverse amount of data.
Holds IS Ilya Sutskever
A good robotaxi demonstration in one city does not mean the company is ready to scale the service.
Holds TL Timothy B. Lee
A huge fleet collecting driving data is not a silver bullet for self-driving, because the data arrives unlabelled.
Holds TL Timothy B. Lee
A large majority of the serious crashes a robotaxi is involved in are caused by the other road user, not by the robotaxi.
Holds TL Timothy B. Lee
A privately owned self-driving car is a hard sell, because the owner inherits the cleaning, calibration and liability a fleet operator normally carries.
Holds TL Timothy B. Lee
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
Holds GM Gary Marcus
A language model is not using language at all, because language requires an intention to communicate.
Holds TC Ted Chiang
A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human.
Holds SC Sean Carroll
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
Process supervision by an LLM judge cannot be run for long, because a judge with billions of parameters is gameable and RL will find its cracks.
Holds
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.
Holds
The memorize-fetch-apply paradigm behind LLMs can reach arbitrary skill given training data, but it cannot adapt to novelty or acquire new skills on the fly.
No longer holds
Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read.
No longer holds AG Alexey Guzey