China is merely the largest of a wide array of entities that may not necessarily like the status quo of Silicon Valley being our tech overlords. There are plenty of places with bright people. Easy to say because a lot of them immigrate to California. But of course the places they come from (China, Europe, India, Russia etc.) have ambitions as well. You'll find natives of each of those in the likes of OpenAI, Google, Microsoft, etc. And quite often at executive levels even.
Silicon Valley has mo moat other than money. It kind of runs on openness and freedom of movement of people. Companies constantly poach people from each other. And there's a constant movement of people (and knowledge) in and out of the area. Money is what attracts these people and keeps them there for a while. But of course that status quo was upset a little bit with VCs turning into penny pinching misers lately and lockdowns proving (to them) that it was cheaper to host your tech teams remotely. Which means knowledge is now more distributed than it used to be.
So, it's not surprising that people outside of Silicon Valley are not waiting patiently for OpenAI to do whatever it is they are doing in between having moral existential crises, trying to oust their CEO, pontificating about AGIs, etc. They are taking things into their own hands. The brute force / VC funding driven approach that OpenAI has used yielded massive results in the last few years. But ever since Meta opensourced their models, OSS models and optimizations have been catching up.
On a hardware resource usage basis, these models started to outperform their bigger peers last year and now the game is up for the training process as well. Meaning they get better results for the same money. A major hurdle here was the model training process. Which the Chinese seem to have proven can be massively optimized as well. Cutting cost by a few orders of magnitude is a big deal. And at the same time doing the same thing at larger scale (aka. throwing more money at the problem) seems to have diminishing returns.
Until that changes, that means the playing field has somewhat leveled now. That's a good thing.
Silicon Valley has mo moat other than money. It kind of runs on openness and freedom of movement of people. Companies constantly poach people from each other. And there's a constant movement of people (and knowledge) in and out of the area. Money is what attracts these people and keeps them there for a while. But of course that status quo was upset a little bit with VCs turning into penny pinching misers lately and lockdowns proving (to them) that it was cheaper to host your tech teams remotely. Which means knowledge is now more distributed than it used to be.
So, it's not surprising that people outside of Silicon Valley are not waiting patiently for OpenAI to do whatever it is they are doing in between having moral existential crises, trying to oust their CEO, pontificating about AGIs, etc. They are taking things into their own hands. The brute force / VC funding driven approach that OpenAI has used yielded massive results in the last few years. But ever since Meta opensourced their models, OSS models and optimizations have been catching up.
On a hardware resource usage basis, these models started to outperform their bigger peers last year and now the game is up for the training process as well. Meaning they get better results for the same money. A major hurdle here was the model training process. Which the Chinese seem to have proven can be massively optimized as well. Cutting cost by a few orders of magnitude is a big deal. And at the same time doing the same thing at larger scale (aka. throwing more money at the problem) seems to have diminishing returns.
Until that changes, that means the playing field has somewhat leveled now. That's a good thing.