A sparse-matrix idea tries to mix tensor-core efficiency with larger hidden capacity
mgostIH · x · 2026-07-28
The post riffs on a quoted idea about sparse weight matrices and a larger “logical hidden dimension.” The author suggests that to make better use of existing tensor cores, one could sparsely select smaller dense blocks so the model gets the benefits of both sparsity and dense computation.
They frame it as “a mixture of matrices” where different blocks learn different things, ending with a light joke that someone should really think about it.
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