MULTIPITA: Reorganizing Compute Without Compressing Identity
This story is from 2026-08-28. It is preserved in the archive; the latest stories are on the live feed.
How NINMENI approaches the computational cost of native character-identity modeling Large language models usually make an implicit compromise: text is compressed into tokens or other larger units before most of the expensive computation happens. NINMENI starts from a different premise. In NINMENI,…
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- 2026-08-28 05:50 · DEV Community — Machine Learning
MULTIPITA: Reorganizing Compute Without Compressing Identity