Give DeepSeek’s engineers credit. Stop fixating on the U.S.–China AI wars.
DeepSeek keeps delivering unbelievable stuff. Every model, including the newly released V3.1, is a gift that keeps on giving.
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DeepSeek just released V3.1. It is open weight and under a more permissive MIT license on Hugging Face. Crazy.
How about we stop fixating on the U.S.–China AI wars and take a moment to recognize the brilliance of DeepSeek’s engineers. In my view, Multi-Head Latent Attention (MLA) is the most innovative idea in transformer models since attention itself.
If MLA had been invented in the U.S., we’d be talking about it non-stop, probably nominating the inventors for the Fields Medal or something.
But because it came from DeepSeek in China, it got brushed aside. Yeah, no big deal. Except it is a big deal. MLA goes back to the good ol’ shrinkage algorithm in statistics and introduces a low-rank compression of key-value caches during inference. You do not have to lug around a million tokens worth of memory - meaning, DeepSeek made it possible to run modern LLMs on your smartphone. And they gave us all the formulas. Everything is open!
And almost no one is talking about it because it is from China and we do not like China. How crazy is that?
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