17 connected korrents · 13 moments from 10 Oct 2023 to 18 Sept 2026.
At the centre
The likeliest bad path is not a coup but sloppiness: AI does everything verifiable well, research races ahead, and the subtle work of keeping AI safe is what gets done badly.
Last stated 11 Aug 2026 · 2 months ago
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Ryan Greenblatt
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The least verifiable part of AI research is the judgement call about what goes into the one big training run.
Last stated 11 Aug 2026 · 2 months ago
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Ryan Greenblatt
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There is no route to AI alignment or safety that goes around reliability: a system that cannot reliably follow a known algorithm cannot be made safe.
Last stated 7 Jun 2025 · a year ago
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Gary Marcus
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Very capable AI will be harder to align than current systems, because the loop of spotting a bad behaviour and patching the training that caused it breaks down.
Last stated 11 Aug 2026 · 2 months ago
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Ryan Greenblatt
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People have grown accustomed to AI being non-deterministic and occasionally wrong, so it carries little brand risk anymore.
Last stated 18 Sept 2026 · a month ago
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Horace Dediu
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Confidence in monitoring, not capability research, will become the binding constraint on AI progress.
Last stated 6 Sept 2026 · 2 months ago
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Jakub Pachocki
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There is now broad agreement within AI safety circles that fully open AI development is undesirable.
Last stated 14 Sept 2026 · a month ago
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Matthew Yglesias
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Misaligned AI behaviour will keep getting rarer and, at the same time, keep getting more extreme.
Last stated 11 Aug 2026 · 2 months ago
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Ryan Greenblatt
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Building AI that can actually be trusted is the goal; containing an AI known to be misaligned is not a substitute for it.
Last stated 24 Jan 2025 · 2 years ago
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Jan Leike
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Same subject: AGI
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 4 Jun 2026 · 5 months ago
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Alex Imas
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Same subject: AGI
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
Last stated 7 Jun 2025 · a year ago
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Gary Marcus
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Same subject: AGI
A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality
Last stated 10 Oct 2023 · 3 years ago
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Chip Huyen
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Same subject: reinforcement learning
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Last stated 3 Aug 2026 · 3 months ago
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Dmitri Dolgov
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Same subject: reinforcement learning
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Last stated 17 Nov 2025 · 11 months ago
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Andrej Karpathy
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Same subject: reinforcement learning
Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model.
Last stated 3 Aug 2026 · 3 months ago
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Dmitri Dolgov
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Same subject: AI agents
A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does.
Last stated 21 May 2026 · 5 months ago
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Rohit Krishnan
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Same subject: AI agents
A company cannot be led by machines, because nobody would have recourse against them.
Last stated 15 Sept 2026 · a month ago
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Tobias Lütke
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Same subject: AI agents
A computer-using agent needs a machine of its own, or you will spend the day fighting it for the mouse cursor.
Last stated 10 Aug 2026 · 2 months ago
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Peter Steinberger