A korrentour readingWhat is a korrent?
Text embeddings produced by different large language models converge on a shared, universal geometric structure regardless of architecture or training data.
Drawn from what Samuel Hammond said
SubjectLLMs
What Samuel Hammond actually said
Word for word, with the source under each one. They did not write this page.
Senior economist at the Foundation for American Innovation
the text embeddings across LLMs appear to largely converge on a "universal geometry" despite differing architectures, parameter counts, and training sets.
Where this was said
↗Hegel and the AI Mindsecondbest.ca
All 3 korrents from this piecethis one is 3rd
Added to korrents 5 Jun 2025 · How quotes work · Something wrong? Tell us
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Related korrents
Our reading — they may agree, disagree or merely touch the same thing. Closest first: a shared subject counts for most, then how near the wording is.