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Mixture of Experts (MoE) models has recently attracted much attention in addressing these challenges, by dynamically selecting and activating the most relevant sub-models to process input data. These models, which seek to increase the parameter to compute ratio use multi-ple sparse MLPs, called experts, instead of a single dense MLP. A classic conception, given the name ”experts” is that. Papers might explore complexity that characterise the work of experts and the contradictory nature of the grand challenges that experts are expected to address.
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