> Spitballing random pr pieces from companies about to IPO is not helpful to anyone, fyi.
replyYou can just use logic to come to the same conclusion. The Chinese labs have a fraction of compute and data. The simplest explanation is distillation.
DeepSeek R1 and DeepSeekMath were groundbreaking models which were substantially stronger than any models available for distillation at the time they were developed. The Chinese labs have advantages as well despite the lack of compute, too.
replyI'm anti-Anthropic and think their accusations are total PR FUD-packing. They don't focus much on the cc fraud because their PR firm landed on pushing the (tech-sounding) word "distillation" to try to scare people in the US and to try to make it a geopolitical issue where trade negotiators can put pressure. The Chinese companies see an advantage in being "open" right now, and it is working. They will not stay open once they see an advantage there. (Contrast with GNU.)
replyBut I've slowly come to realize that AI+"dark resources"(scare quotes)=something bad! And this is imminent (maybe I'm naive and it is already ubiquitous).
We see here, with Kimi, that there's growing traction with the idea of eliminating types of training to avoid evil. I'm skeptical of that.
Have you trained models? If not then you can't really speak to how effective distillation is (answer: it is very effective)
replyWhy don't we see more American companies doing distillation? If you could make an opus 5.5 cheaply by distillation in china, you can do so even easier in America where you have more gpus.
replylol. Have you? What kind of distill you are talking about? It’s only effective in the surface, small scale model or output preference. Not useful for long reasoning chain.
replyWhy lol? Yes. All major labs use SFT... (look at job postings)
reply> Not useful for long reasoning chain.
I have a feeling you don't actually know anything about ML
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