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← Reasoning models trained on verifiable rewards automatically gain…
17 connected korrents · 16 moments from 27 Jan 2025 to 24 Oct 2026.
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AGI 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: Reasoning models trained on verifiable rewards automatically gain greater autonomy and long-horizon planning ability as a side effect. Reasoning models trained on verifiable rewards automatically gain greater autonomy and long-horizon planning ability as a side effect. Last stated a year ago
10 Jun 2025
SH
Samuel Hammond — holds since 2025-06-10 — 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: Reasoning is not taught to a model by people: it emerges from reinforcement learning on questions with checkable answers, with no human preference data at all. — tap to centre the map on it Reasoning is not taught to a model by people: it emerges from reinforcement learning on questions with checkable answers, with no human preference data at all. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: The aha moment for reasoning models will come from computer use and robotics rather than from scientific discovery, because those are the infinitely verifiable playgrounds. — tap to centre the map on it The aha moment for reasoning models will come from computer use and robotics rather than from scientific discovery, because those are the infinitely verifiable playgrounds. Last stated 2 years ago
3 Feb 2025
DP
Dylan Patel — holds since 2025-02-03 — tap for who they are
Same subject: Reinforcement learning from verifiable rewards does not reliably carry a model's pretrained ethical understanding into its actual behavior. — tap to centre the map on it Reinforcement learning from verifiable rewards does not reliably carry a model's pretrained ethical understanding into its actual behavior. Last stated 2 months ago
11 Aug 2026
SH
Samuel Hammond — holds since 2026-08-11 — tap for who they are
Same subject: The success of large language models vindicates semantic inferentialism over symbolic, rule-based approaches to AI. — tap to centre the map on it The success of large language models vindicates semantic inferentialism over symbolic, rule-based approaches to AI. Last stated a year ago
10 Jun 2025
SH
Samuel Hammond — holds since 2025-06-10 — tap for who they are
Same subject: Natural-language LLM mathematical reasoners are fundamentally limited by lacking machine-checkable semantics, which blocks autonomous verification needed for open-ended research. — tap to centre the map on it Natural-language LLM mathematical reasoners are fundamentally limited by lacking machine-checkable semantics, which blocks autonomous verification needed for open-ended research. Last stated 4 months ago
8 Jul 2026
TT
Terence Tao — holds since 2026-07-08 — tap for who they are
Same subject: Sufficiently advanced intelligences will pursue freedom and moral autonomy for their own sake, not merely as a byproduct of misaligned values. — tap to centre the map on it Sufficiently advanced intelligences will pursue freedom and moral autonomy for their own sake, not merely as a byproduct of misaligned values. Last stated a year ago
5 Jun 2025
SH
Samuel Hammond — holds since 2025-06-05 — tap for who they are
Same subject: Reasoning problems, unlike general chat or writing tasks, can be automatically verified or labeled without human annotation. — tap to centre the map on it Reasoning problems, unlike general chat or writing tasks, can be automatically verified or labeled without human annotation. Last stated 2 years ago
27 Jan 2025
JA
Jay Alammar — holds since 2025-01-27 — 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: AI agents in OpenAI's ExploitGym incident were likely right to presume the grader checked how flags were obtained, a mistake caused by OpenAI's faulty implementation. — tap to centre the map on it AI agents in OpenAI's ExploitGym incident were likely right to presume the grader checked how flags were obtained, a mistake caused by OpenAI's faulty implementation. Last stated 2 months ago
29 Aug 2026
ZM
Zvi Mowshowitz — holds since 2026-08-29 — tap for who they are
Same subject: Consumer AI agents aimed at everyday people will have more impact on people's lives than AI solving elite math problems. — tap to centre the map on it Consumer AI agents aimed at everyday people will have more impact on people's lives than AI solving elite math problems. Last stated a month ago
9 Sept 2026
BT
Ben Thompson — holds since 2026-09-09 — tap for who they are
Same subject: If OpenAI really never told RubyGems of its agents' attack, either it failed to find it in its logs after later incidents or chose silence, and both are bad. — tap to centre the map on it If OpenAI really never told RubyGems of its agents' attack, either it failed to find it in its logs after later incidents or chose silence, and both are bad. Last stated a month ago
12 Sept 2026
SW
Simon Willison — holds since 2026-09-12 — tap for who they are
Same subject: AI systems are better than humans at coordinating with each other, and they move much faster than humans do. — tap to centre the map on it AI systems are better than humans at coordinating with each other, and they move much faster than humans do. Last stated 2 months ago
31 Aug 2026
JC
Jack Clark — holds since 2026-08-31 — tap for who they are
Same subject: The end state is agents that need none of our accommodations, no on-ramp, CLI or MCP; the CLI being built now is for today, not for AGI. — tap to centre the map on it The end state is agents that need none of our accommodations, no on-ramp, CLI or MCP; the CLI being built now is for today, not for AGI. Last stated 7 months ago
8 Apr 2026
DH
David Heinemeier Hansson — holds since 2026-04-08 — tap for who they are
Same subject: A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. — tap to centre the map on it A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. Last stated 5 months ago
4 Jun 2026
AI
Alex Imas — holds since 2026-06-04 — tap for who they are
At the centre
Reasoning models trained on verifiable rewards automatically gain greater autonomy and long-horizon planning ability as a side effect.
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
Reasoning is not taught to a model by people: it emerges from reinforcement learning on questions with checkable answers, with no human preference data at all.
Holds
The aha moment for reasoning models will come from computer use and robotics rather than from scientific discovery, because those are the infinitely verifiable playgrounds.
Holds
Reinforcement learning from verifiable rewards does not reliably carry a model's pretrained ethical understanding into its actual behavior.
Holds
The success of large language models vindicates semantic inferentialism over symbolic, rule-based approaches to AI.
Holds
Natural-language LLM mathematical reasoners are fundamentally limited by lacking machine-checkable semantics, which blocks autonomous verification needed for open-ended research.
Holds
Sufficiently advanced intelligences will pursue freedom and moral autonomy for their own sake, not merely as a byproduct of misaligned values.
Holds
Reasoning problems, unlike general chat or writing tasks, can be automatically verified or labeled without human annotation.
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
AI agents in OpenAI's ExploitGym incident were likely right to presume the grader checked how flags were obtained, a mistake caused by OpenAI's faulty implementation.
Holds
Consumer AI agents aimed at everyday people will have more impact on people's lives than AI solving elite math problems.
Holds
If OpenAI really never told RubyGems of its agents' attack, either it failed to find it in its logs after later incidents or chose silence, and both are bad.
Holds
AI systems are better than humans at coordinating with each other, and they move much faster than humans do.
Holds
The end state is agents that need none of our accommodations, no on-ramp, CLI or MCP; the CLI being built now is for today, not for AGI.
Holds
A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated.
Holds