I think what's actually needed is two things: an EU training infrastructure that allows training of 10T+ models, and an EU inference infrastructure that is sufficient that it's possible to do RL on them.

This effectively reduces the problem to a specialized supercomputing infrastructure problem which I think is relatively easy to solve. I think the chips are coming. I think Euclyd will be able to do the inference chip and I think the training chip won't be harder. It's just a matter of accepting the need to order a huge number of them, being willing to think a little bit like the kind of people who operate corners. So we can be there next year, I think. What we then lack is a training chip-- maybe OpenChip can do it, maybe they can't, but there are reasonable but still unfinished projects. Maybe if Euclyd finishes an inference chip in 2027 we can have the state pay them to make a training version, put in fp32, put in communication tiles. If their design is real and works (which it should, since it's basically a fancier version of Groq, as it's described, and since even Groq works) I think the advantage these chips is likely to have would be enough that a training version would be NVIDIA-beating.

We probably need some solution for the data-- i.e. to allow people to do things that are against copyright law in a limited way, but I think it's a better idea to start EU firms than to try to attract Anthropic.

Because of the need for capital the hardware-software carousel is necessary. We can't pay for NVIDIA chips and then have NVIDIA feed that money into US firms. We have to feed money into EU chips that either carousel the money into EU AI firms or who just offer cheap chips.