Tap a claim on the ring to put it at the centre.
← A large context window does not replace fine-tuning, because…
17 connected korrents · 17 moments from 11 Oct 2018 to 21 Oct 2026. Nearly all of them are about LLMs .
Everything filed under AI agents
AI agents
Everything filed under AI alignment
AI alignment
Everything filed under OpenAI
OpenAI
Everything filed under transformers
transformers 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: A large context window does not replace fine-tuning, because fine-tuning serves the separate purpose of instilling preferences and demonstrating a task. A large context window does not replace fine-tuning, because fine-tuning serves the separate purpose of instilling preferences and demonstrating a task. Last stated 3 years ago
22 Mar 2024
EG
Elad Gil — holds since 2024-03-22 — tap for who they are
Same subject: A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. — tap to centre the map on it A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. Last stated 3 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A model you have to fine-tune for each thing you want it to do is not a general-purpose model. — tap to centre the map on it A model you have to fine-tune for each thing you want it to do is not a general-purpose model. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: Every announcement of a longer context window hides the cost, which is that the model gets worse at following instructions. — tap to centre the map on it Every announcement of a longer context window hides the cost, which is that the model gets worse at following instructions. Last stated 2 years ago
19 Jun 2024
AS
Aravind Srinivas — holds since 2024-06-19 — tap for who they are
Same subject: The scarce skill is now context switching across parallel agents, not sustained deep work. — tap to centre the map on it The scarce skill is now context switching across parallel agents, not sustained deep work. Last stated 8 months ago
4 Mar 2026
BC
Boris Cherny — holds since 2026-03-04 — tap for who they are
Same subject: Fine-tuning with human feedback is a promising direction for aligning language models with human intent. — tap to centre the map on it Fine-tuning with human feedback is a promising direction for aligning language models with human intent. Last stated 5 years ago
4 Mar 2022
JL
Jan Leike — holds since 2022-03-04 — 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: Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own. — tap to centre the map on it Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — 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: A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does. — tap to centre the map on it A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does. Last stated 5 months ago
21 May 2026
RK
Rohit Krishnan — holds since 2026-05-21 — tap for who they are
Same subject: A company cannot be led by machines, because nobody would have recourse against them. — tap to centre the map on it A company cannot be led by machines, because nobody would have recourse against them. Last stated a month ago
15 Sept 2026
TL
Tobias Lütke — holds since 2026-09-15 — tap for who they are
Same subject: A computer-using agent needs a machine of its own, or you will spend the day fighting it for the mouse cursor. — tap to centre the map on it A computer-using agent needs a machine of its own, or you will spend the day fighting it for the mouse cursor. Last stated 2 months ago
10 Aug 2026
PS
Peter Steinberger — holds since 2026-08-10 — tap for who they are
Same subject: A company that uses an algorithm to nudge customers into behavior that isn't good for them is doing something bad. — tap to centre the map on it A company that uses an algorithm to nudge customers into behavior that isn't good for them is doing something bad. Last stated a year ago
7 Oct 2025
MM
Mr. Money Mustache — holds since 2025-10-07 — tap for who they are
Same subject: A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail. — tap to centre the map on it A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail. Last stated 2 years ago
7 May 2024
BS
Buck Shlegeris — holds since 2024-05-07 — 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 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
At the centre
A large context window does not replace fine-tuning, because fine-tuning serves the separate purpose of instilling preferences and demonstrating a task.
Holds Read this korrent →
A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to.
Holds
A model you have to fine-tune for each thing you want it to do is not a general-purpose model.
Holds
Every announcement of a longer context window hides the cost, which is that the model gets worse at following instructions.
Holds
The scarce skill is now context switching across parallel agents, not sustained deep work.
Holds
Fine-tuning with human feedback is a promising direction for aligning language models with human intent.
Holds
Unidirectional restrictions are sub-optimal for sentence-level tasks and harmful for token-level tasks that need bidirectional context.
Holds
Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own.
Holds
Full fine-tuning of large language models has become too costly, making parameter-efficient fine-tuning methods necessary.
Holds
A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does.
Holds
A company cannot be led by machines, because nobody would have recourse against them.
Holds
A computer-using agent needs a machine of its own, or you will spend the day fighting it for the mouse cursor.
Holds
A company that uses an algorithm to nudge customers into behavior that isn't good for them is doing something bad.
Holds
A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail.
Holds
A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score.
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