In plain English
Rather than using the whole model for every word, this design sends each piece to the few parts best suited to it. The model can hold a lot of knowledge while doing only a fraction of the work each time, which makes it faster and cheaper to run.
Example
A model has 64 expert sections but uses only 2 for each word it writes. It knows as much as a much bigger model but costs closer to a small one to run.
In short
Only wake who's needed. A big model that uses just a few of its parts at a time.
Why it matters
Many of today's most capable models use this design, including well-known open-weight models like DeepSeek and Mixtral. It's a big part of how AI keeps getting more capable without costs rising at the same pace.
Common confusion
Mixture of experts vs. multi-agent system. The "experts" aren't separate AIs talking to each other. They're parts of one model, picked automatically for each word, and they don't specialize in tidy topics like math or law.