AI scaling myths
A blog post by Arvind Narayanan and Sayash Kapoor, AI Snake Oil, dated 27 June 2024. post_date in the Substack page metadata.
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- AI scaling myths AI Snake Oil (the authors' Substack, now at normaltech.ai) · published 2024-06-27 · Retrieved for the candidate pack on 2026-10-29 (SHA-256 14de787679324dbfbfdaaf1093d0c62ecba3e07a55732cdfa9ab74cc467f913d). Current Substack page (requested at aisnakeoil.com, served at normaltech.ai), dated 2024-06-27 in its metadata; retrieved 2026-10-29.
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- Arguments about catastrophic risk from advanced AI →1 record on this document
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- Situational Awareness: The Decade AheadNarayanan and Kapoor's post of June 2024 addresses Aschenbrenner's essay of 2024, which it names, in its further-reading note.2024-06-27 · publication · Stated in source · Supported Inspect claim & evidence ↗Aschenbrenner, Situational Awareness (2024): document page →
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- Capabilities will plateauNarayanan and Kapoor's post of June 2024 argues that scaling laws do not predict emergent capabilities, that high-quality training data is running short and model sizes are under downward pressure, and states that there is virtually no chance that scaling alone will lead to AGI.2024-06-27 · publication · Stated in source · Supported Inspect claim & evidence ↗Capabilities will plateau: propositions page →
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