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← The only reliable way to improve an AI model's reasoning today is to train it on more data and make it bigger.
17 connected korrents · 16 moments from 18 Mar 2024 to 24 Oct 2026.
Everything filed under LLMs
LLMs
Everything filed under reinforcement learning
reinforcement learning
Everything filed under Anthropic
Anthropic
Everything filed under OpenAI
OpenAI
Everything filed under AI and science
AI and science
Everything filed under AI alignment
AI alignment
Everything filed under AI agents
AI agents
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: The only reliable way to improve an AI model's reasoning today is to train it on more data and make it bigger. The only reliable way to improve an AI model's reasoning today is to train it on more data and make it bigger. Last stated 3 years ago
22 Mar 2024
EG
Elad Gil — holds since 2024-03-22 — tap for who they are
Same subject: Reasoning models are an upgrade from conventional LLMs achieved by adding post-training via reinforcement learning and optionally inference scaling. — tap to centre the map on it Reasoning models are an upgrade from conventional LLMs achieved by adding post-training via reinforcement learning and optionally inference scaling. Last stated today
24 Oct 2026
SR
Sebastian Raschka — holds since 2026-10-24 — tap for who they are
Same subject: The one safe bet about AI is that models will improve, so what a company has to build is an organisation that gets better as models get better. — tap to centre the map on it The one safe bet about AI is that models will improve, so what a company has to build is an organisation that gets better as models get better. Last stated a year ago
16 Oct 2025
DF
Dylan Field — holds since 2025-10-16 — tap for who they are
Same subject: AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. — tap to centre the map on it AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. Last stated 11 months ago
23 Nov 2025
EH
Elliot Hershberg — holds since 2025-11-23 — tap for who they are
Same subject: The strongest reason to keep training much smarter models quickly is to build defences against other AI. — tap to centre the map on it The strongest reason to keep training much smarter models quickly is to build defences against other AI. Last stated 2 months ago
6 Sept 2026
JP
Jakub Pachocki — holds since 2026-09-06 — tap for who they are
Same subject: You improve a model you cannot retrain by writing better guidelines and skills for it, not by adjusting its parameters. — tap to centre the map on it You improve a model you cannot retrain by writing better guidelines and skills for it, not by adjusting its parameters. Last stated 3 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: Bigger is smarter, always: bringing your special domain knowledge to the model is the wrong side of the bitter lesson. — tap to centre the map on it Bigger is smarter, always: bringing your special domain knowledge to the model is the wrong side of the bitter lesson. Last stated 7 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: Existing AI models are already more than good enough, doing more for writing code than the author can make use of. — tap to centre the map on it Existing AI models are already more than good enough, doing more for writing code than the author can make use of. Last stated 2 months ago
8 Sept 2026
GO
Gergely Orosz — holds since 2026-09-08 — tap for who they are
Same subject: Current AI models still fall short of expert human performance. — tap to centre the map on it Current AI models still fall short of expert human performance. Last stated 2 years ago
27 Jan 2025
NE
Nelson Elhage — holds since 2025-01-27 — tap for who they are
Same subject: A PHP vulnerability found with GPT-5.6 Sol will cause havoc this week. — tap to centre the map on it A PHP vulnerability found with GPT-5.6 Sol will cause havoc this week. Last stated 3 days ago
21 Oct 2026
PS
Peter Steinberger — holds since 2026-10-21 — 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: A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score. — tap to centre the map on it A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score. Last stated 2 months ago
26 Aug 2026
HK
Henrik Karlsson — holds since 2026-08-26 — tap for who they are
Same subject: A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. — tap to centre the map on it A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. Last stated 3 months ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. — tap to centre the map on it A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. Last stated 11 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — 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 2 months 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
At the centre
The only reliable way to improve an AI model's reasoning today is to train it on more data and make it bigger.
Holds Read this korrent →
Reasoning models are an upgrade from conventional LLMs achieved by adding post-training via reinforcement learning and optionally inference scaling.
Holds
The one safe bet about AI is that models will improve, so what a company has to build is an organisation that gets better as models get better.
Holds
AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points.
Holds
The strongest reason to keep training much smarter models quickly is to build defences against other AI.
Holds
You improve a model you cannot retrain by writing better guidelines and skills for it, not by adjusting its parameters.
Holds
Bigger is smarter, always: bringing your special domain knowledge to the model is the wrong side of the bitter lesson.
Holds
Existing AI models are already more than good enough, doing more for writing code than the author can make use of.
Holds
Current AI models still fall short of expert human performance.
Holds
A PHP vulnerability found with GPT-5.6 Sol will cause havoc this week.
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
A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score.
Holds
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Holds
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
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