Sparse mixture-of-experts models

What experts have said about Sparse mixture-of-experts models

1 statement · 1 positive

1. Reiner PopePositiveApr 29, 2026· Dwarkesh Podcast

   Increasing sparsity is beneficial until insufficient users prevent larger batches.

   “From the point of view of the analysis we've done here, this is pure win. Keep doing it, keep doing it until you run out of available users, basically.”

   Listen at 31:06

   Open the episode · Reiner Pope – The math behind how LLMs are trained and served

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