Mixtral of Experts — A Primer
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Mixtures of Experts (MoE) models offer a unique approach to handling complex prediction problems.
Their foundation was introduced in the early 1990s by Jacobs et al. (Jacobs et al., 1991). [https://doi.org/10.1162/neco.1991.3.1.79]
The core idea behind MoE models is to utilize a collection of expert models (E) to make a prediction (y) through a weighted sum, where the weights are assigned by a gating network (G). This effectively breaks down a large, intricate problem into smaller, more manageable sub-problems, embodying the “divide and conquer” strategy.
The true potential of MoE models, however, was unlocked with the introduction of top-k routing. This innovative technique was…
