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Imagine having a whole team of specialists at your disposal, each an expert in a different field, and a smart coordinator who directs questions to the right expert. That’s essentially the idea behind Mixture-of-Experts (MoE) architecture in AI. In traditional large language models (LLMs), one giant model handles everything, which means using all its billions of parameters for every single query – even if only a fraction of that knowledge is needed.
https://sam-solutions.com/blog/moe-llm-architecture/
By SaM SolutionsImagine having a whole team of specialists at your disposal, each an expert in a different field, and a smart coordinator who directs questions to the right expert. That’s essentially the idea behind Mixture-of-Experts (MoE) architecture in AI. In traditional large language models (LLMs), one giant model handles everything, which means using all its billions of parameters for every single query – even if only a fraction of that knowledge is needed.
https://sam-solutions.com/blog/moe-llm-architecture/