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The fun part about this is that we can see who is right in about a year. If the leading labs continue making progress at hardening their models against distillation, and then they start pulling away again, we see who is right. If China is able to pass the US and release an independently better model than anything the US has, then your theory is correct.

Both sides have extremely smart people. One side has more $$$ and exclusive access to the best chips. For progress to converge without a corresponding breakthrough suggests there's something else at work.

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Indeed we will, my prediction is that we'll see a model from China that definitively surpasses any US model by the end of the year. China has an absolute population advantage here along with having a much better education system. And China now dominates in published AI papers.

The US enjoyed an early advantage due to excessive money being poured into AI which led to the current bubble, and access to the hardware that was needed to train these models initially.

At this point, neither of these factors actually matter that much. The naive approach of simply making models bigger has hit a wall, and now you need ingenuity in figuring out better architecture for them. Precisely because Chinese companies have had to deal with more limited resources, they put a lot more effort into researching different kinds of optimizing techniques. And of course, China is also catching up in chip making, and Huawei clusters are already competitive with Nvidia for training. So, that gap is closing as well.

The big difference is that an absolutely insane amount of money has been spent in the US, while China managed to do this on a fraction of the budget. The AI Investment Surge graph here puts things in perspective. https://hai.stanford.edu/news/inside-the-ai-index-12-takeawa...

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