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← Explicit signals like follows and subscriptions are as brittle and…
17 connected korrents · 16 moments on record from 12 Jun 2017 to 15 Sept 2026.
Everything filed under LLMs
LLMs
Everything filed under transformers
transformers
Everything filed under measuring intelligence
measuring intelligence
Everything filed under scaling laws
scaling laws 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: Explicit signals like follows and subscriptions are as brittle and hard to maintain as manually tuned filter rules. Explicit signals like follows and subscriptions are as brittle and hard to maintain as manually tuned filter rules. Last stated 4 months ago
2 Jun 2026
AW
Adam Wiggins — holds since 2026-06-02 — tap for who they are
Same subject: Manually configured filtering rules mostly fail because a person's preferences change over time and the rules require ongoing upkeep. — tap to centre the map on it Manually configured filtering rules mostly fail because a person's preferences change over time and the rules require ongoing upkeep. Last stated 8 months ago
13 Jan 2026
AW
Adam Wiggins — holds since 2026-01-13 — tap for who they are
Same subject: Full fine-tuning of large language models has become too costly, making parameter-efficient fine-tuning methods necessary. — tap to centre the map on it Full fine-tuning of large language models has become too costly, making parameter-efficient fine-tuning methods necessary. Last stated 3 years ago
5 Dec 2023
SR
Sebastian Ruder — holds since 2023-12-05 — tap for who they are
Same subject: As models get better at following instructions, techniques like finetuning and constrained sampling for structured outputs will become less necessary — tap to centre the map on it As models get better at following instructions, techniques like finetuning and constrained sampling for structured outputs will become less necessary Last stated 3 years ago
16 Jan 2024
CH
Chip Huyen — holds since 2024-01-16 — tap for who they are
Same subject: Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context. — tap to centre the map on it Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context. 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 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: AI's business results are lagging because organisations have a low tolerance for non-determinism, not because the models are not good enough. — tap to centre the map on it AI's business results are lagging because organisations have a low tolerance for non-determinism, not because the models are not good enough. Last stated 6 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — 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 11 months ago
16 Oct 2025
DF
Dylan Field — holds since 2025-10-16 — tap for who they are
Same subject: The specific rules taught as clean code are simply bad programming practices, and they get worse when you apply them together. — tap to centre the map on it The specific rules taught as clean code are simply bad programming practices, and they get worse when you apply them together. Last stated 4 weeks ago
26 Aug 2026
CM
Casey Muratori — holds since 2026-08-26 — tap for who they are
Same subject: A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution. — tap to centre the map on it A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution. Last stated 9 years ago
12 Jun 2017
IP
Illia Polosukhin — holds since 2017-06-12 — tap for who they are
JU
Jakob Uszkoreit — holds since 2017-06-12 — tap for who they are
NP
Niki Parmar — holds since 2017-06-12 — tap for who they are
AV
Ashish Vaswani — holds since 2017-06-12 — tap for who they are
NS
Noam Shazeer — holds since 2017-06-12 — tap for who they are
AG
Aidan N. Gomez — holds since 2017-06-12 — tap for who they are
+2
2 more on record
Same subject: Self-attention can yield more interpretable models. — tap to centre the map on it Self-attention can yield more interpretable models. Last stated 9 years ago
12 Jun 2017
IP
Illia Polosukhin — holds since 2017-06-12 — tap for who they are
JU
Jakob Uszkoreit — holds since 2017-06-12 — tap for who they are
NP
Niki Parmar — holds since 2017-06-12 — tap for who they are
AV
Ashish Vaswani — holds since 2017-06-12 — tap for who they are
NS
Noam Shazeer — holds since 2017-06-12 — tap for who they are
AG
Aidan N. Gomez — holds since 2017-06-12 — tap for who they are
+2
2 more on record
Same subject: Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions. — tap to centre the map on it Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions. Last stated 9 years ago
12 Jun 2017
IP
Illia Polosukhin — holds since 2017-06-12 — tap for who they are
JU
Jakob Uszkoreit — holds since 2017-06-12 — tap for who they are
NP
Niki Parmar — holds since 2017-06-12 — tap for who they are
AV
Ashish Vaswani — holds since 2017-06-12 — tap for who they are
NS
Noam Shazeer — holds since 2017-06-12 — tap for who they are
AG
Aidan N. Gomez — holds since 2017-06-12 — tap for who they are
+2
2 more on record
Same subject: A true artificial general intelligence cannot exist without being recognized as a moral subject. — tap to centre the map on it A true artificial general intelligence cannot exist without being recognized as a moral subject. Last stated a year ago
10 Jun 2025
SH
Samuel Hammond — holds since 2025-06-10 — tap for who they are
Same subject: A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model. — tap to centre the map on it A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model. Last stated 6 days ago
15 Sept 2026
PG
Paul Graham — holds since 2026-09-15 — tap for who they are
Same subject: Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect. — tap to centre the map on it Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect. Last stated 7 years ago
5 Nov 2019
FC
François Chollet — holds since 2019-11-05 — 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 10 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 3 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 6 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
At the centre
Explicit signals like follows and subscriptions are as brittle and hard to maintain as manually tuned filter rules.
Holds Read this korrent →
Manually configured filtering rules mostly fail because a person's preferences change over time and the rules require ongoing upkeep.
Holds
Full fine-tuning of large language models has become too costly, making parameter-efficient fine-tuning methods necessary.
Holds
As models get better at following instructions, techniques like finetuning and constrained sampling for structured outputs will become less necessary
Holds
Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context.
Holds
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
AI's business results are lagging because organisations have a low tolerance for non-determinism, not because the models are not good enough.
Holds
AI cannot get a product to the quality bar on its own, because it still works in the realm of averages.
Holds
The specific rules taught as clean code are simply bad programming practices, and they get worse when you apply them together.
Holds
A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.
Holds
Self-attention can yield more interpretable models.
Holds
Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.
Holds
A true artificial general intelligence cannot exist without being recognized as a moral subject.
Holds
A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model.
Holds
Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect.
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