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← Scaling laws are still working, but the models people actually use run…
17 connected korrents · 17 moments from 11 Oct 2018 to 19 Sept 2026. Nearly all of them are about scaling laws .
Everything filed under Google
Google
Everything filed under LLMs
LLMs
Everything filed under benchmarks
benchmarks
Everything filed under AI agents
AI agents In tension 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: 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. 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
In tension: Future AI, say in fifteen years, will not be built on the LLM stack; it will have to move to symbolic learning. — tap to centre the map on it Future AI, say in fifteen years, will not be built on the LLM stack; it will have to move to symbolic learning. Last stated 2 months ago
7 Aug 2026
FC
François Chollet — holds since 2026-08-07 — 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: 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 7 months ago
23 Mar 2026
JH
Jensen Huang — holds since 2026-03-23 — tap for who they are
Same subject: AI scaling laws require exponentially more compute and resources to produce only linear gains in model intelligence. — tap to centre the map on it AI scaling laws require exponentially more compute and resources to produce only linear gains in model intelligence. Last stated a month ago
19 Sept 2026
NL
Nathan Lambert — holds since 2026-09-19 — tap for who they are
Same subject: As models keep scaling up, modularity will become essential to how they are developed. — tap to centre the map on it As models keep scaling up, modularity will become essential to how they are developed. Last stated 4 years ago
23 Feb 2023
SR
Sebastian Ruder — holds since 2023-02-23 — 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 3 months 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 2 months ago
7 Aug 2026
FC
François Chollet — holds since 2026-08-07 — tap for who they are
Same subject: Current techniques restrict pre-trained representation power because standard language models are unidirectional. — tap to centre the map on it Current techniques restrict pre-trained representation power because standard language models are unidirectional. 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 company that is a genuine climate champion should not need to be forced into climate action. — tap to centre the map on it A company that is a genuine climate champion should not need to be forced into climate action. Last stated 2 months ago
19 Aug 2026
EA
Emily Atkin — holds since 2026-08-19 — tap for who they are
Same subject: A company's staff-engineer bar should be set against the best companies in the industry rather than against its own history, which is what makes title inflation a real cost. — tap to centre the map on it A company's staff-engineer bar should be set against the best companies in the industry rather than against its own history, which is what makes title inflation a real cost. Last stated 7 months ago
1 Apr 2026
TP
Thuan Pham — holds since 2026-04-01 — tap for who they are
Same subject: A crewed rocket cannot be made safe by making the booster reliable, so the only real way to improve safety is to carry an escape system. — tap to centre the map on it A crewed rocket cannot be made safe by making the booster reliable, so the only real way to improve safety is to carry an escape system. Last stated 3 years ago
14 Dec 2023
JB
Jeff Bezos — holds since 2023-12-14 — tap for who they are
Same subject: Generative AI's climate harm comes mainly from wasteful system design and forced-on features, not from the computational cost of individual queries. — tap to centre the map on it Generative AI's climate harm comes mainly from wasteful system design and forced-on features, not from the computational cost of individual queries. Last stated 4 months ago
1 Jul 2026
KJ
Ketan Joshi — holds since 2026-07-01 — tap for who they are
Same subject: Google had the data, the technology and the engineers to ship ChatGPT in 2019, and bureaucracy alone is why it did not. — tap to centre the map on it Google had the data, the technology and the engineers to ship ChatGPT in 2019, and bureaucracy alone is why it did not. Last stated 2 years ago
20 Aug 2024
PL
Pieter Levels — holds since 2024-08-20 — tap for who they are
Same subject: LLMs can write a large fraction of the tedious code a developer will ever need to write, and most code on most projects is tedious. — tap to centre the map on it LLMs can write a large fraction of the tedious code a developer will ever need to write, and most code on most projects is tedious. Last stated a year ago
2 Jun 2025
TP
Thomas Ptacek — holds since 2025-06-02 — 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: Chatbot interfaces are the wrong tool for meaningful coding work, because you are mostly hoping the model recalls the right answer and correcting it requires a human in the loop. — tap to centre the map on it Chatbot interfaces are the wrong tool for meaningful coding work, because you are mostly hoping the model recalls the right answer and correcting it requires a human in the loop. Last stated 9 months ago
5 Feb 2026
MH
Mitchell Hashimoto — holds since 2026-02-05 — tap for who they are
At the centre
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 Read this korrent →
Future AI, say in fifteen years, will not be built on the LLM stack; it will have to move to symbolic learning.
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
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
AI scaling laws require exponentially more compute and resources to produce only linear gains in model intelligence.
Holds
As models keep scaling up, modularity will become essential to how they are developed.
Holds
Bet on a system that is maximally learned and minimally constrained, and add structure only where it improves the scaling laws.
Holds
Current AI techniques are four to six orders of magnitude away from optimal in data efficiency and test-time compute efficiency.
Holds
Current techniques restrict pre-trained representation power because standard language models are unidirectional.
Holds
A company that is a genuine climate champion should not need to be forced into climate action.
Holds
A company's staff-engineer bar should be set against the best companies in the industry rather than against its own history, which is what makes title inflation a real cost.
Holds
A crewed rocket cannot be made safe by making the booster reliable, so the only real way to improve safety is to carry an escape system.
Holds
Generative AI's climate harm comes mainly from wasteful system design and forced-on features, not from the computational cost of individual queries.
Holds
Google had the data, the technology and the engineers to ship ChatGPT in 2019, and bureaucracy alone is why it did not.
Holds
LLMs can write a large fraction of the tedious code a developer will ever need to write, and most code on most projects is tedious.
Holds
Agents are going to be incorporated into mainstream interfaces
Holds
Chatbot interfaces are the wrong tool for meaningful coding work, because you are mostly hoping the model recalls the right answer and correcting it requires a human in the loop.
Holds