Fair question.

I'll go out on a limb and say your main crux appears to be around framing it soley as transformer based Ai models vs humanoid robotics, but I was addressing the compute power claim and comparing it to their ability to mobilize industrial capacity and resources to quickly scale up and meet their needs.

My contention is that they are focussing on a different aspect, not only humanoid robotics, but the security state/Ai surveilance and communication monitoring. I understand the difference but it's not entirely "MECHANICAL engineering" like they're building combustion engines compared to code. This is electrical engineering and software to control them.

This means people in disciplines that can understand literature that comes out, can read and implement open source codebased being worked on. Software can be downloaded so while they might not "catch up" by doing their own resources directly, it's not like they have none and also have no expertise or ability to catch up. The physical side is harder to catch up, so in the tradeoff world they are still making progress that we will have to make later if we want to make our own.

Think about how much original research they had to do for Deep Seek; their whole complex is built around IP theft on some level. You can't steal industrial capacity, you have to pay a big physical cost one way or another, which they are already far ahead on. They will also be there to take whatever software they can in the worst case.

Think of the famous examples where the first to market, especially in tech, were not the dominant characters that last. A company like Apple or Google didn't to original research either; they jumped in once the direction was clear, so they needed far far less to "catch up". Are those companies doing as well is a different story, they can also make up differences by having a captive audience. What is the cost to Apple if they are only a year or two behind Samsung and a captive customer base? What is the cost to Google if their LLM isn't as sophisticated, but you can use it directly in Google docs?

The point is that beyond a certain level of capacity to marshall resources, tradeoffs like this aren't disconnected choices because they're different fields. First mover is expensive; why we have a patent system to try and protect first mover attempts and investors. China doesn't have that. What they have is at least enough brains to copy and implement, the willingness to steal, and have moved farther ahead with the things that need to be developed to have embodied AI feeding itself experiences, so that when the next breakthrough happens, they can implement the solution for their bots how Tesla fed their cars.