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A CERN for AI-assisted science

A CERN for AI-assisted science

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TL;DR · WeSearch summary

The author argues that the scientific community must urgently establish publicly funded frontier AI systems to counter the dominance of private companies in research. Current reliance on private AI creates significant risks regarding data confidentiality, the protection of unpublished work, and the misalignment of corporate incentives with scientific values. Public access to these tools is essential to reduce resource asymmetries and ensure that early-career researchers are not disadvantaged by the rapid pace of AI-driven discoveries.

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Hacker News (AI / LLM) files mainly under ai. We currently carry 5,769 of its stories.

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Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.

Record

Original publisherWhat's new
Canonical URLhttps://terrytao.wordpress.com/2026/09/17/a-cern-for-ai-assisted-science/
Publication timeMon, 21 Sep 2026 00:00:39 +0000
Retrieval time2026-09-21T00:18:47.148Z
Last seen2026-09-21T00:18:47.148Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
ClustertidF2LBZrrsY · 1 stories
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

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Machine-readable
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WeSearch interpretation
WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
Retrieval and training permissions are not asserted unless the publisher confirms them.

WeSearch handling by dimension

Indexing May the item be indexed (stored, ranked, made findable)? Allowed
Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

[This is a guest post by Dimitris Koukoulopoulos. This blog post was initially written in a different file format and converted using AI. — T.] At the 2026 World Cup semifinal, England led Argentina 1-0 with less than twenty minutes left. And then the momentum completely changed: England switched to a much more defensive formation, withdrawing attacking players and retreating deeper. The Argentinians started attacking in waves. They equalized in the 85th minute and scored the winner in stoppage time. England’s defeat offers a valuable lesson: when trying to avoid the worst outcome, fear and passivity are not your friends.

Excerpt limited to ~120 words for fair-use compliance. The full article is at What's new.

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