Transcription
Here's what's happening. What they realized is that the AI scaling race is not a chip race. It's a full stack systems code race. Where if you can't compete head-to-head on chips for now, what do you do? You compete on systems design.
You say, "Okay, we don't have leading edge chips here yet. So, let's try to compete on systems." The code design, the chip that you have might be Huawei with the compute infrastructure with the training run. And then you design that to have a bunch of performance improvements at every layer of the stack.
And then what you do is you do adversarial distillation at scale where you take western models and then you from various different endpoints you distill the state-of-the-art. Then you try to get as many performance gains as possible on that data and then you release that back out to the world as open models and then you see what people react to.
Then you get feedback and then you do the next run and the next run and then you catch up. And at the point you catch up you say, "Wait a minute, we're starting to be at the frontier. Why do we need to open source anymore? This is good enough for our local domestic needs." And that's why Huawei chips are able to produce capabilities improvements today in China that rival some of the best chips.