The speakers discuss the rise of mixture of experts (MOE) as a commercially successful sparse model in the field of AI. They explain the divergence between the amount of compute required for training and inference and the need to keep all the weights of the MOE model loaded. The speakers anticipate that the rise of MOEs will significantly impact the inference market and potentially change how we think about pricing and paradigms in AI.

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