Mixture of Experts (MoE) models are a type of neural network architecture designed to improve efficiency and scalability by activating only a small subset of the entire model for each input. Instead of using all available parameters at once, MoE models route each input through a few specialized "expert" subnetworks chosen by a gating mechanism. This allows the model to be much larger and more powerful without significantly increasing the computation needed for each prediction, making it ideal for tasks that benefit from both specialization and scale.

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Sources:

1. https://arxiv.org/pdf/2407.06204
2. https://arxiv.org/pdf/2406.18219
3. https://tinyurl.com/5eyzspwp
4. https://huggingface.co/blog/moe