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// ✳ Mixture of Experts

Switch Transformer

A simplified MoE that routes each token to a single expert.

2021 Intermediate core

Original paper ↓ What to learn first →

IN PLAIN WORDS

Simplifies routing to top-1 and adds load-balancing loss and precision tricks, stably training trillion-parameter models faster at equal compute.

Used in: Google MoE research

TIMELINE · prerequisites → this → what builds on it

2017 Sparsely-Gate…2021 Switch Transformer

01Original paper

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

William Fedus, Barret Zoph, Noam Shazeer · 2021

arXiv ↗ ✓ Verified · arXiv API

02Where it sits

Learn the left column first; the right column builds on this one.

Learn first

Switch Transformer

Then you can learn

  • Nothing in the atlas builds on it yet

Related:Mixtral (Top-2 MoE)Auxiliary-Loss-Free Load Balancing

Sparsely-Gated …Mixtral (Top-2 …Auxiliary-Loss-… Switch Transformer

Left: prerequisites · right: builds on this · dashed: related. Full map →

03Learning resources

Official docs, explainers, courses and reference code. All links checked.

Explainers

04Where the course teaches it

U43 MoE & Beyond-Transformer Architectures Sparse experts, load balancing, Mamba/SSMs, linear attention and hybrid architectures, diffusion language models. 10 h18 algorithms5 papers
For AI / data

Data updated: AI algorithms & curriculum(UTC+8)