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← The scaling curve really is S-shaped, but there are at least two…
17 connected korrents · 17 moments from 22 Mar 2025 to 2 Oct 2026.
Everything filed under scaling laws
scaling laws
Everything filed under AI and jobs
AI and jobs
Everything filed under LLMs
LLMs
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: The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed. The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed. Last stated 7 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. — tap to centre the map on it The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. Last stated 2 months ago
4 Sept 2026
FL
Fei-Fei Li — holds since 2026-09-04 — tap for who they are
Same subject: We are already in an intelligence explosion and have been for decades, so AI will show up as more of the same exponential rather than a break in it. — tap to centre the map on it We are already in an intelligence explosion and have been for decades, so AI will show up as more of the same exponential rather than a break in it. Last stated a year ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve. — tap to centre the map on it Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve. Last stated a year ago
5 Jun 2025
SP
Sundar Pichai — holds since 2025-06-05 — tap for who they are
Same subject: Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared. — tap to centre the map on it Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared. Last stated 2 months ago
26 Aug 2026
DH
David Heinemeier Hansson — holds since 2026-08-26 — tap for who they are
Same subject: Intelligence is going to scale by exactly one thing, and that thing is compute. — tap to centre the map on it Intelligence is going to scale by exactly one thing, and that thing is compute. Last stated 7 months ago
23 Mar 2026
JH
Jensen Huang — holds since 2026-03-23 — tap for who they are
Same subject: The AI research cycle from idea to experiment will likely soon be 10x faster, but that may not make researchers 10x more productive in the field's net understanding. — tap to centre the map on it The AI research cycle from idea to experiment will likely soon be 10x faster, but that may not make researchers 10x more productive in the field's net understanding. Last stated 4 weeks ago
22 Sept 2026
NL
Nathan Lambert — holds since 2026-09-22 — 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: Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew. — tap to centre the map on it Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew. Last stated a year ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: A company must cut half its engineers to pay for the other half's tokens, and that is what the layoffs are actually about. — tap to centre the map on it A company must cut half its engineers to pay for the other half's tokens, and that is what the layoffs are actually about. Last stated 7 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: A likely outcome is that many occupations are eventually mostly replaced by AI while humans still have plenty to do. — tap to centre the map on it A likely outcome is that many occupations are eventually mostly replaced by AI while humans still have plenty to do. Last stated a month ago
7 Sept 2026
NS
Noah Smith — holds since 2026-09-07 — tap for who they are
Same subject: A lot of jobs will probably be created because of AI. — tap to centre the map on it A lot of jobs will probably be created because of AI. Last stated 4 weeks ago
27 Sept 2026
MG
Molly Graham — holds since 2026-09-27 — tap for who they are
Same subject: AI will not eliminate software engineering jobs, but engineers who are highly skilled with AI tools could displace those who are not. — tap to centre the map on it AI will not eliminate software engineering jobs, but engineers who are highly skilled with AI tools could displace those who are not. Last stated 6 months ago
27 Apr 2026
JS
Jon Seager — holds since 2026-04-27 — tap for who they are
Same subject: Leaning on AI trades knowledge for speed, and the price may be a generation of programmers in which juniors stay juniors forever. — tap to centre the map on it Leaning on AI trades knowledge for speed, and the price may be a generation of programmers in which juniors stay juniors forever. Last stated 2 years ago
22 Mar 2025
TH
ThePrimeagen — holds since 2025-03-22 — tap for who they are
Same subject: Many things only worked because there is a limit to the rate at which humans can operate. — tap to centre the map on it Many things only worked because there is a limit to the rate at which humans can operate. Last stated 3 weeks ago
2 Oct 2026
PG
Paul Graham — holds since 2026-10-02 — tap for who they are
Same subject: An agent can understand a maximally simplified explanation and still be unable to come up with it — that gap is what is left of the expert's job. — tap to centre the map on it An agent can understand a maximally simplified explanation and still be unable to come up with it — that gap is what is left of the expert's job. Last stated 7 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: An AI you have to supervise at 90 percent is not 90 percent task completion: you are still doing the thing. — tap to centre the map on it An AI you have to supervise at 90 percent is not 90 percent task completion: you are still doing the thing. Last stated a month ago
8 Sept 2026
RU
Roman Ugarte — holds since 2026-09-08 — tap for who they are
Same subject: As AI agents take on bigger delegated tasks, the human bottleneck shifts to writing specs and reviewing output fast, hollowing out the middle of the work. — tap to centre the map on it As AI agents take on bigger delegated tasks, the human bottleneck shifts to writing specs and reviewing output fast, hollowing out the middle of the work. Last stated 6 months ago
3 May 2026
EY
Eugene Yan — holds since 2026-05-03 — tap for who they are
At the centre
The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed.
Holds Read this korrent →
The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture.
Holds
We are already in an intelligence explosion and have been for decades, so AI will show up as more of the same exponential rather than a break in it.
Holds
Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve.
Holds
Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared.
Holds
Intelligence is going to scale by exactly one thing, and that thing is compute.
Holds
The AI research cycle from idea to experiment will likely soon be 10x faster, but that may not make researchers 10x more productive in the field's net understanding.
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
Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew.
Holds
A company must cut half its engineers to pay for the other half's tokens, and that is what the layoffs are actually about.
Holds
A likely outcome is that many occupations are eventually mostly replaced by AI while humans still have plenty to do.
Holds
A lot of jobs will probably be created because of AI.
Holds
AI will not eliminate software engineering jobs, but engineers who are highly skilled with AI tools could displace those who are not.
Holds
Leaning on AI trades knowledge for speed, and the price may be a generation of programmers in which juniors stay juniors forever.
Holds
Many things only worked because there is a limit to the rate at which humans can operate.
Holds
An agent can understand a maximally simplified explanation and still be unable to come up with it — that gap is what is left of the expert's job.
Holds
An AI you have to supervise at 90 percent is not 90 percent task completion: you are still doing the thing.
Holds
As AI agents take on bigger delegated tasks, the human bottleneck shifts to writing specs and reviewing output fast, hollowing out the middle of the work.
Holds