Equation 14 · Dense, Sparse, and Distilled: Comparing Approaches to Frontier Model Capacity
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Symbol N_a
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The economics are attractive and frequently overstated. Training compute scales with , not N , so a sparse model can hold far more knowledge for the same training FLOPs. Patterson and colleagues, computing energy and carbon for several large models including Switch Transformer and GPT-3, found that large but sparsely activated networks can consume less than one tenth the energy of large dense networks without sacrificing accuracy [ 10 ] .
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