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by numeri·2y ago·view on hn ↗
That has nothing to do with the idea of ensembling multiple specialized/single-purpose models. Mixture of Experts is an method of splitting the feed-forwards in a model such that only a (hopefully) relevant subset of parameters is run for each token.

The model learns how to split them on its own, and usually splits based not on topic or domain, but on grammatical function or category of symbol (e.g., punctuation, counting words, conjunctions, proper nouns, etc.).

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An ensemble of specialists is different to a mixture of experts?

I thought half the point of MoE was to make the training tractable by allowing the different experts to be trained independently?