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← In verifiable domains model capability scaling should remain…
17 connected korrents · 16 moments on record from 28 Jul 2023 to 4 Sept 2026.
Everything filed under scaling laws
scaling laws
Everything filed under Google
Google
Everything filed under prompt injection
prompt injection
Everything filed under reinforcement learning
reinforcement learning
Everything filed under benchmarks
benchmarks
Everything filed under cybersecurity
cybersecurity 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: In verifiable domains model capability scaling should remain unbounded, because the space of enumerable patterns is infinite by construction. In verifiable domains model capability scaling should remain unbounded, because the space of enumerable patterns is infinite by construction. Last stated 2 weeks ago
27 Aug 2026
FC
François Chollet — holds since 2026-08-27 — tap for who they are
Same subject: When a capability evaluation benchmark is saturated without real-world verification, a model should be presumed to have that capability until shown otherwise. — tap to centre the map on it When a capability evaluation benchmark is saturated without real-world verification, a model should be presumed to have that capability until shown otherwise. Last stated 3 days ago
4 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-04 — tap for who they are
Same subject: Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve. — tap to centre the map on it Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve. Last stated a year ago
5 Jun 2025
SP
Sundar Pichai — holds since 2025-06-05 — tap for who they are
Same subject: The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. — tap to centre the map on it The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. Last stated 3 days ago
4 Sept 2026
FL
Fei-Fei Li — holds since 2026-09-04 — tap for who they are
Same subject: The least verifiable part of AI research is the judgement call about what goes into the one big training run. — tap to centre the map on it The least verifiable part of AI research is the judgement call about what goes into the one big training run. Last stated 4 weeks ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: Models leak and algorithms get copied, but hundreds of millions of audited autonomous miles cannot be replicated — earned trust is the real moat. — tap to centre the map on it Models leak and algorithms get copied, but hundreds of millions of audited autonomous miles cannot be replicated — earned trust is the real moat. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed. — tap to centre the map on it The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed. Last stated 6 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: Running a model until its performance plateaus is no longer a usable evaluation rule, because a well-scaffolded model keeps improving for weeks. — tap to centre the map on it Running a model until its performance plateaus is no longer a usable evaluation rule, because a well-scaffolded model keeps improving for weeks. Last stated 2 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: The tradeoff in cyber-capable models cannot be designed away: the model that can do something nefarious is the same model that hardens the system against it. — tap to centre the map on it The tradeoff in cyber-capable models cannot be designed away: the model that can do something nefarious is the same model that hardens the system against it. Last stated 3 weeks ago
18 Aug 2026
MK
Michael Kratsios — holds since 2026-08-18 — 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 10 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — tap for who they are
Same subject: Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. — tap to centre the map on it Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. Last stated 6 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. — tap to centre the map on it Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: Auto-mode does not yet convincingly fix prompt-injection risk for coding agents. — tap to centre the map on it Auto-mode does not yet convincingly fix prompt-injection risk for coding agents. Last stated 4 weeks ago
8 Aug 2026
SW
Simon Willison — holds since 2026-08-08 — tap for who they are
Same subject: Current prompt-injection defenses for AI agents (such as auto mode) are now reliable enough that agents can practically be assumed safe from successful injection attacks. — tap to centre the map on it Current prompt-injection defenses for AI agents (such as auto mode) are now reliable enough that agents can practically be assumed safe from successful injection attacks. Last stated 3 days ago
4 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-04 — tap for who they are
Same subject: Do not run a personal agent on a cheap or local model: weak models are gullible and easy to prompt-inject. — tap to centre the map on it Do not run a personal agent on a cheap or local model: weak models are gullible and easy to prompt-inject. Last stated 7 months ago
12 Feb 2026
PS
Peter Steinberger — holds since 2026-02-12 — tap for who they are
Same subject: A crewed rocket cannot be made safe by making the booster reliable, so the only real way to improve safety is to carry an escape system. — tap to centre the map on it A crewed rocket cannot be made safe by making the booster reliable, so the only real way to improve safety is to carry an escape system. Last stated 3 years ago
14 Dec 2023
JB
Jeff Bezos — holds since 2023-12-14 — tap for who they are
Same subject: A monopolist that can no longer grow by winning new users can only grow by making its product worse for the users it already has. — tap to centre the map on it A monopolist that can no longer grow by winning new users can only grow by making its product worse for the users it already has. Last stated 3 years ago
28 Jul 2023
CD
Cory Doctorow — holds since 2023-07-28 — tap for who they are
Same subject: A startup does not have to set out to build the greatest business in history; a merely good business is a legitimate thing to aim at. — tap to centre the map on it A startup does not have to set out to build the greatest business in history; a merely good business is a legitimate thing to aim at. Last stated 2 years ago
19 Jun 2024
AS
Aravind Srinivas — holds since 2024-06-19 — tap for who they are
At the centre
In verifiable domains model capability scaling should remain unbounded, because the space of enumerable patterns is infinite by construction.
Holds Read this korrent →
When a capability evaluation benchmark is saturated without real-world verification, a model should be presumed to have that capability until shown otherwise.
Holds ZM Zvi Mowshowitz
Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve.
Holds
The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture.
Holds FL Fei-Fei Li
The least verifiable part of AI research is the judgement call about what goes into the one big training run.
Holds RG Ryan Greenblatt
Models leak and algorithms get copied, but hundreds of millions of audited autonomous miles cannot be replicated — earned trust is the real moat.
Holds DD Dmitri Dolgov
The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed.
Holds SY Steve Yegge
Running a model until its performance plateaus is no longer a usable evaluation rule, because a well-scaffolded model keeps improving for weeks.
Holds NB Noam Brown
The tradeoff in cyber-capable models cannot be designed away: the model that can do something nefarious is the same model that hardens the system against it.
Holds MK Michael Kratsios
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago.
Holds
Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving.
Holds
Auto-mode does not yet convincingly fix prompt-injection risk for coding agents.
Holds
Current prompt-injection defenses for AI agents (such as auto mode) are now reliable enough that agents can practically be assumed safe from successful injection attacks.
Holds ZM Zvi Mowshowitz
Do not run a personal agent on a cheap or local model: weak models are gullible and easy to prompt-inject.
Holds
A crewed rocket cannot be made safe by making the booster reliable, so the only real way to improve safety is to carry an escape system.
Holds JB Jeff Bezos
A monopolist that can no longer grow by winning new users can only grow by making its product worse for the users it already has.
Holds CD Cory Doctorow
A startup does not have to set out to build the greatest business in history; a merely good business is a legitimate thing to aim at.
Holds AS Aravind Srinivas