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Whether models trained on different modalities converge to the same representation of the world is central to AI. The Platonic Representation Hypothesis (PRH) conjectures that they do as they scale, but without a proof it offers neither a guarantee nor a recipe. We turn the hypothesis into a theorem. First, we prove a \emph{Platonic Representation Theorem}: Joint-Embedding Predictive Architectures (JEPAs) trained separately on any number of modalities learn the same representation up to one…
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It's probably a good idea to put a 'Flock Sock' on them, just to be safe.
AI summary The article discusses how AI coding is rapidly changing, with a focus on the importance of stable, reliable tools like Pi as a harness.
AI summary The author wrote two short stories, one in 7 months and another in 10 days, using groff for typesetting.
It is hoped game testing can provide insight into recent AI agent headlines, good and bad.
