Amazing Milestone! Million Experts Model

A top researcher at Google DeepMind just released an important paper, “Mixture of a Million Experts.” As the paper’s title announces, it describes an approach that resulted in the first-known Transformer model with more than a million experts.

For context, the number of experts currently seen in smaller models varies between 4 and 32, and ranges up to 128 for most of the bigger ones.

This video reviews the Mixture-of-Experts method, including why and where it’s used, and the computational challenges associated with doing this. Next, it summarizes the findings of another important paper from earlier this year, where a new scaling law was introduced for Mixture-of-Experts models. That sets us up to review the “Million Experts” paper by Xu He.

The video then describes two key strategies that enabled scale to over a million experts by creating experts that are only a single neuron large. Next, it shares a process map for the new approach, and concludes with ideas about where this might be most relevant, including applications that involve continuous data streams.

[hausenmusic]

Great video! Thank you for the clear explanation. The calm tone made it easier to undertand.

[AIMasterGroup]

Here’s a link to the paper I featured in this video: “Mixture of A Million Experts, ” by Xu He at Google DeepMind