17 connected korrents · 19 moments from 11 Oct 2018 to 23 Sept 2026.
At the centre
The race between AI companies to build ever more powerful systems is a choice they made, not an inevitable law of nature, and it is a race everyone loses.
Last stated 23 Sept 2026 · a week ago
Holds
Yoshua Bengio
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Similar wording
Systematising principled decision-making with AI is now the line between staying competitive and not; there is no position in between.
Last stated 10 Jun 2026 · 4 months ago
Holds
Ray Dalio
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Similar wording
Competition between AI companies and countries is pushing accelerated AI development without sufficient caution, risking loss of control.
Last stated 3 Jun 2025 · a year ago
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Yoshua Bengio
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Similar wording
Competing with AI in producing outputs is a losing game; human advantages should be used to work with AI on things neither could do alone.
Last stated 18 Sept 2026 · 2 weeks ago
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Ethan Mollick
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Similar wording
As AI makes building faster and cheaper, choosing the right thing to build matters more than ever, because a competitor will get it right if you don't.
Last stated 18 Jul 2025 · a year ago
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Jason Evanish
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Similar wording
There is far less trade-off than people assume between a safer AI race and widely shared gains: a big lead can be held by a widely owned public company.
Last stated 4 Jun 2026 · 4 months ago
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Phil Trammell
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Similar wording
There is no natural, clear dividing line between AI and other kinds of software.
Last stated 8 Sept 2026 · 4 weeks ago
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Robin Hanson
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Similar wording
Even with human-like learners, competition will split the AI market into specialised niches rather than hand it to one company.
Last stated 25 Nov 2025 · 10 months ago
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Ilya Sutskever
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Similar wording
People have grown accustomed to AI being non-deterministic and occasionally wrong, so it carries little brand risk anymore.
Last stated 18 Sept 2026 · 2 weeks ago
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Horace Dediu
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Same subject: LLMs
A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI.
Last stated 1 Jan 2026 · 9 months ago
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Jason Lemkin
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Same subject: LLMs
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 15 Jul 2026 · 3 months ago
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Dex Horthy
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Same subject: LLMs
A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved.
Last stated 10 Aug 2026 · 2 months ago
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Fei-Fei Li
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Same subject: scaling laws
AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard.
Last stated 2 Feb 2025 · 2 years ago
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Ajeya Cotra
Scott Alexander
Miles Brundage
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Same subject: scaling laws
As models keep growing, AI is running out of enough high-quality unique training tokens to keep up.
Last stated 24 Jun 2026 · 3 months ago
Holds
Lilian Weng
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Same subject: scaling laws
Current techniques restrict pre-trained representation power because standard language models are unidirectional.
Last stated 11 Oct 2018 · 8 years ago
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Kristina Toutanova
Ming-Wei Chang
Kenton Lee
Jacob Devlin
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Same subject: OpenAI
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.
Last stated 12 Feb 2026 · 8 months ago
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Andrej Karpathy
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Same subject: OpenAI
AI labs are extremely dependent on chain-of-thought monitoring, which may not last much longer as models edge into steganographic obfuscation.
Last stated 10 Sept 2026 · 3 weeks ago
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Zvi Mowshowitz
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Same subject: OpenAI
AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun.
Last stated 18 Mar 2024 · 3 years ago
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Sam Altman