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← Data is becoming more valuable not only for training models but as a complement to cheaper intelligence.
17 connected korrents · 15 moments from 10 Dec 2015 to 9 Oct 2026.
Everything filed under LLMs
LLMs
Everything filed under neural networks
neural networks
Everything filed under Anthropic
Anthropic
Everything filed under OpenAI
OpenAI
Everything filed under scaling laws
scaling laws
Everything filed under design
design 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: Data is becoming more valuable not only for training models but as a complement to cheaper intelligence. Data is becoming more valuable not only for training models but as a complement to cheaper intelligence. Last stated 2 days ago
9 Oct 2026
PC
Patrick Collison — holds since 2026-10-09 — tap for who they are
Same subject: As AI makes code cheaper to produce, understanding and architectural design become more valuable. — tap to centre the map on it As AI makes code cheaper to produce, understanding and architectural design become more valuable. Last stated 2 years ago
27 Jan 2025
NE
Nelson Elhage — holds since 2025-01-27 — tap for who they are
Same subject: The internet is already past peak truth, and picking out training data worth learning from will only get harder. — tap to centre the map on it The internet is already past peak truth, and picking out training data worth learning from will only get harder. Last stated 5 months ago
13 May 2026
AH
Anders Hejlsberg — holds since 2026-05-13 — tap for who they are
Same subject: Training is no longer limited by data but by compute, because most of the data models learn from is now synthetic. — tap to centre the map on it Training is no longer limited by data but by compute, because most of the data models learn from is now synthetic. Last stated 7 months ago
23 Mar 2026
JH
Jensen Huang — holds since 2026-03-23 — tap for who they are
Same subject: What sits in a model's context is far clearer to it than its training data, which is trillions of tokens stirred into a soup of parameters. — tap to centre the map on it What sits in a model's context is far clearer to it than its training data, which is trillions of tokens stirred into a soup of parameters. Last stated 2 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. — tap to centre the map on it The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. Last stated 12 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: Proprietary data is not an advantage in training large language models, because no company's holdings are large enough to matter. — tap to centre the map on it Proprietary data is not an advantage in training large language models, because no company's holdings are large enough to matter. Last stated a year ago
2 Sept 2025
BE
Benedict Evans — holds since 2025-09-02 — tap for who they are
Same subject: Today's models see a thousand times more data than an eighteen-year-old and are no better for it, so far more data-efficient algorithms must be possible. — tap to centre the map on it Today's models see a thousand times more data than an eighteen-year-old and are no better for it, so far more data-efficient algorithms must be possible. Last stated 2 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: Scaling up spending on expert human data has not been a major driver of progress in AI research. — tap to centre the map on it Scaling up spending on expert human data has not been a major driver of progress in AI research. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. — tap to centre the map on it A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. — tap to centre the map on it Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — 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: "I don't know" becomes a kind of superpower when you can work with Claude Code to figure things out. — tap to centre the map on it "I don't know" becomes a kind of superpower when you can work with Claude Code to figure things out. Last stated 7 months ago
19 Mar 2026
KP
Kris Puckett — holds since 2026-03-19 — tap for who they are
Same subject: A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. — tap to centre the map on it A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. Last stated a month ago
3 Sept 2026
DR
Dax Raad — holds since 2026-09-03 — tap for who they are
Same subject: A skill is a set of repeatable, specific instructions that augments what Claude Code can do. — tap to centre the map on it A skill is a set of repeatable, specific instructions that augments what Claude Code can do. Last stated 7 months ago
19 Mar 2026
KP
Kris Puckett — holds since 2026-03-19 — tap for who they are
Same subject: A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable. — tap to centre the map on it A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable. Last stated 11 years ago
10 Dec 2015
JS
Jian Sun — holds since 2015-12-10 — tap for who they are
KH
Kaiming He — holds since 2015-12-10 — tap for who they are
Same subject: A small enough winning ticket learns faster than the network it was cut out of, and ends up more accurate than it. — tap to centre the map on it A small enough winning ticket learns faster than the network it was cut out of, and ends up more accurate than it. Last stated 9 years ago
9 Mar 2018
MC
Michael Carbin — holds since 2018-03-09 — tap for who they are
JF
Jonathan Frankle — holds since 2018-03-09 — 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
At the centre
Data is becoming more valuable not only for training models but as a complement to cheaper intelligence.
Holds Read this korrent →
As AI makes code cheaper to produce, understanding and architectural design become more valuable.
Holds
The internet is already past peak truth, and picking out training data worth learning from will only get harder.
Holds
Training is no longer limited by data but by compute, because most of the data models learn from is now synthetic.
Holds
What sits in a model's context is far clearer to it than its training data, which is trillions of tokens stirred into a soup of parameters.
Holds
The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out.
Holds
Proprietary data is not an advantage in training large language models, because no company's holdings are large enough to matter.
Holds
Today's models see a thousand times more data than an eighteen-year-old and are no better for it, so far more data-efficient algorithms must be possible.
Holds
Scaling up spending on expert human data has not been a major driver of progress in AI research.
Holds
A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests.
Holds
Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers.
Holds
Agents are going to be incorporated into mainstream interfaces
Holds
"I don't know" becomes a kind of superpower when you can work with Claude Code to figure things out.
Holds
A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year.
Holds
A skill is a set of repeatable, specific instructions that augments what Claude Code can do.
Holds
A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable.
Holds
A small enough winning ticket learns faster than the network it was cut out of, and ends up more accurate than it.
Holds
A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.
Holds