A field guide to AI positions

Foundation models

AI basics.

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Publication dates and source age

Sources counted: 1

Newest dated source: 2021-08-16

Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.

Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.

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Prepared with AI assistance. Not independently fact-checked. Original sources and qualifications are below.

In plain language

Models trained on broad data that can be adapted for many tasks. Reusing one model can also spread its weaknesses across applications. [1]

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Explanation based on the linked sources. Claim ID: claim-term-foundation-models-1a5192ba3d7825ca26b24a72. Edition 0.20.0.

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Limits & distinctions

A foundation model is a reusable component. Its broad training does not establish equal performance across applications. [1]

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Explanation based on the linked sources. Claim ID: claim-term-foundation-models-09422ce4d5c74cb753a9bb98. Edition 0.20.0.

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A fuller explanation

A shared trained model becomes a starting point for different uses, through prompts or further training. The term includes more than language models. [1]

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Explanation based on the linked sources. Claim ID: claim-term-foundation-models-1e4c26398ee834b2e16dc7b8. Edition 0.20.0.

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How it relates to the map

Map context: shared models connect development choices to many downstream applications. [1]

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Editorial interpretation or qualification. Claim ID: claim-term-foundation-models-25f52a21ad9f2e54a62ed1b2. Edition 0.20.0.

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Sources and what we read

  1. 1. On the Opportunities and Risks of Foundation Models

    Rishi Bommasani and coauthors / Stanford CRFM / arXiv · First-hand source · Published 2021-08-16 · Updated 2022-07-12 · Material last read 2026-09-15

    Source is over 18 months old.

    Publication dates and source age

    Sources counted: 1

    Newest dated source: 2021-08-16

    Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.

    Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.

    Read scope is described in the source note.

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    Read abstract, introduction and shared-model risk discussion. Dates follow arXiv versions. A terminology proposal and research synthesis.

    Source ID: foundation-model-report

Edition and machine-readable evidence

Content version 0.20.0. Evidence cutoff 2026-09-15; this does not mean every source was read on that day.

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