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← If reasoning can be separated from facts, the frontier labs lose their…
17 connected korrents · 16 moments from 11 Oct 2018 to 17 Sept 2026.
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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: If reasoning can be separated from facts, the frontier labs lose their advantage, because nobody needs a million-GPU cluster any more. If reasoning can be separated from facts, the frontier labs lose their advantage, because nobody needs a million-GPU cluster any more. Last stated 2 years ago
19 Jun 2024
AS
Aravind Srinivas — holds since 2024-06-19 — tap for who they are
Same subject: NVIDIA hardware is unlikely to become cheaper, keeping local AI data centers out of reach for small companies. — tap to centre the map on it NVIDIA hardware is unlikely to become cheaper, keeping local AI data centers out of reach for small companies. Last stated 5 months ago
25 May 2026
SS
Salvatore Sanfilippo — holds since 2026-05-25 — tap for who they are
Same subject: Nvidia's real miss was not seeing that a frontier lab could never be funded by venture capital, so its compute suppliers had to become its investors. — tap to centre the map on it Nvidia's real miss was not seeing that a frontier lab could never be funded by venture capital, so its compute suppliers had to become its investors. Last stated 6 months ago
15 Apr 2026
JH
Jensen Huang — holds since 2026-04-15 — tap for who they are
Same subject: A frontier lab should not spend its researchers harvesting results out of today's models; the payoff is in building the next one. — tap to centre the map on it A frontier lab should not spend its researchers harvesting results out of today's models; the payoff is in building the next one. 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: Inference is a high-margin business even for a middleman: renting GPUs at scale, some models carry an eighty per cent margin over their sticker price. — tap to centre the map on it Inference is a high-margin business even for a middleman: renting GPUs at scale, some models carry an eighty per cent margin over their sticker price. Last stated 5 months ago
27 May 2026
DR
Dax Raad — holds since 2026-05-27 — tap for who they are
Same subject: There is no private evidence behind frontier-lab confidence in fast AI progress; the evidence is public and outsiders have simply not absorbed it. — tap to centre the map on it There is no private evidence behind frontier-lab confidence in fast AI progress; the evidence is public and outsiders have simply not absorbed it. Last stated 2 years ago
20 Dec 2024
MB
Miles Brundage — holds since 2024-12-20 — tap for who they are
Same subject: Falling back to older 7-nanometre chips would not rescue AI compute, because the real gap between chip generations is twentyfold, not the threefold the flops suggest. — tap to centre the map on it Falling back to older 7-nanometre chips would not rescue AI compute, because the real gap between chip generations is twentyfold, not the threefold the flops suggest. Last stated 7 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: There will be no overnight intelligence explosion, because a model's best work takes so much test-time compute that time itself is the bottleneck. — tap to centre the map on it There will be no overnight intelligence explosion, because a model's best work takes so much test-time compute that time itself is the bottleneck. Last stated 4 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. — tap to centre the map on it A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. Last stated 10 months ago
1 Jan 2026
JL
Jason Lemkin — holds since 2026-01-01 — tap for who they are
Same subject: A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. — tap to centre the map on it A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. Last stated 3 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. — tap to centre the map on it A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. Last stated a month ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — 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 8 months ago
12 Feb 2026
AK
Andrej Karpathy — holds since 2026-02-12 — tap for who they are
Same subject: AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun. — tap to centre the map on it AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected. — tap to centre the map on it An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected. Last stated 4 years ago
21 Mar 2023
BC
Bryan Caplan — holds since 2023-03-21 — tap for who they are
Same subject: A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models. — tap to centre the map on it A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models. 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: A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression. — tap to centre the map on it A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression. Last stated 2 months ago
7 Sept 2026
KK
Kevin Kelly — holds since 2026-09-07 — tap for who they are
Same subject: Large language models are grown rather than built, and nobody really knows how the resulting working AI functions. — tap to centre the map on it Large language models are grown rather than built, and nobody really knows how the resulting working AI functions. Last stated a month ago
8 Sept 2026
SA
Scott Alexander — holds since 2026-09-08 — tap for who they are
At the centre
If reasoning can be separated from facts, the frontier labs lose their advantage, because nobody needs a million-GPU cluster any more.
Holds Read this korrent →
NVIDIA hardware is unlikely to become cheaper, keeping local AI data centers out of reach for small companies.
Holds
Nvidia's real miss was not seeing that a frontier lab could never be funded by venture capital, so its compute suppliers had to become its investors.
Holds
A frontier lab should not spend its researchers harvesting results out of today's models; the payoff is in building the next one.
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
Inference is a high-margin business even for a middleman: renting GPUs at scale, some models carry an eighty per cent margin over their sticker price.
Holds
There is no private evidence behind frontier-lab confidence in fast AI progress; the evidence is public and outsiders have simply not absorbed it.
Holds
Falling back to older 7-nanometre chips would not rescue AI compute, because the real gap between chip generations is twentyfold, not the threefold the flops suggest.
Holds
There will be no overnight intelligence explosion, because a model's best work takes so much test-time compute that time itself is the bottleneck.
Holds
A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI.
Holds
A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to.
Holds
A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls.
Holds
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.
Holds
AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun.
Holds
An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected.
Holds
A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models.
Holds
A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression.
Holds
Large language models are grown rather than built, and nobody really knows how the resulting working AI functions.
Holds