Will releasing the weights of large language models grant widespread access to pandemic agents?
A preprint by Anjali Gopal and 8 co-authors, arXiv:2310.18233, dated 25 October 2023. arXiv submission history: v1 Wed, 25 Oct 2023; v2 1 Nov 2023.
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- Will releasing the weights of large language models grant widespread access to pandemic agents? arXiv:2310.18233 · published 2023-10-25 · Retrieved for the candidate pack on 2026-10-29 (SHA-256 76930b27d12c6aac9f02b0bf7e7c0b83b2c8ca0f7840c9ef98e4729cb30894d6). arXiv v1 abstract page (the v1 PDF as retrieved has no text layer); quotation limited to the abstract. The cross-family check retrieved it again on 2026-10-31; the bytes differ, and the check compared the quoted passages.
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- Arguments about catastrophic risk from advanced AI →1 record on this document
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- On the Societal Impact of Open Foundation ModelsKapoor, Bommasani and co-authors' paper of February 2024 cites Gopal and co-authors' paper as finding that open language models can generate accurate information about pandemic pathogens, and states that such information is publicly available without open language models.2024-02-27 · publication · Stated in source · Supported Inspect claim & evidence ↗On the Societal Impact of Open Foundation Models: document page →
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- Open models reduce riskGopal and co-authors' paper of 25 October 2023 states that its results suggest that releasing the weights of advanced foundation models, no matter how robustly safeguarded, will trigger the proliferation of knowledge sufficient to acquire pandemic agents and other biological weapons.2023-10-25 · publication · Stated in source · Supported Inspect claim & evidence ↗Open models reduce risk: propositions page →
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