Yep, and they're probably simulating/emulating their CPU design on GPUs already.

> This requires moving beyond the notion of shared mutable memory and linear instruction sequences.

Sure looks like it.

But they are ignoring the basic lesson of "new" CPU designs from Transputer to i432 to Itanium to Transmeta.

A new CPU design is easy, it is the compiler to use it that is the hard hard part.

Looked at another way, CUDA is a huge reason NVidia is so big right now. Their GPUs are broadly similar to AMD. Their software libraries are better.

But good luck to them, perhaps they have some great new idea. We need one.

> it is the compiler to use it that is the hard hard part

We're in a wildly different world from the one Itanium got to live in and compilers are something with a super tight automated verification loop that can make LLMs thrive. Add that plus cheap formal verification and I think this concern goes away almost completely.

> CUDA is a huge reason NVidia is so big right now. Their GPUs are broadly similar to AMD. Their software libraries are better.

This was pre-2026 story. CUDA isn't a moat anymore.

Now it's mostly market dynamics: People always ship ad optimize things for Nvidia because it's the most widely used platform, and people buy it because it has the most software.

This is much less of a barrier than it used to be though. Buggy AMD GPU drivers remain a problem though.

Not necessarily, there are other kinds of accelerator designs like dataflow architectures or systolic arrays.

technically no : a GPU is basically multiple core running the very same program, with the only distinction being caused by a distinct identifier per core.

here they can do multiple programs