It's barely gaining adoption though. The lack of buzz is a chicken and egg issue for Mojo. I fiddled shortly with it (mainly to get it working some of my pythong scripts), and it was suprisingly easy. It'll shoot up one day for sure if Latner doesn't give up early on it.
Isn't the compiler still closed source? I and many other ML devs have no interest in a closed-source compiler. We have enough proprietary things from NVIDIA.
Yes, but Latner said multiple time it's closed until it matures (he apparently did this with llvm and swift too). So not unusal. His open source target is end of 2026. In all fairness, I have 0 doubts that he would deliver.
Use-cases like this are why Mojo isn't used in production, ever. What does Nvidia gain from switching to a proprietary frontend for a compiler backend they're already using? It's a legal headache.
Second-rate libraries like OpenCL had industry buy-in because they were open. They went through standards committees and cooperated with the rest of the industry (even Nvidia) to hear-out everyone's needs. Lattner gave up on appealing to that crowd the moment he told Khronos to pound sand. Nobody should be wondering why Apple or Nvidia won't touch Mojo with a thirty-nine and a half foot pole.
Kernels now written in Mojo were all in hand written in MLIR like in this repo. They made a full language because that's not scalable, a sane language is totally worth it. Nvidia will probably end up buying them in a few years.
CUDA Tile was exactly designed to give parity to Python in writing CUDA kernels, acknowledging the relevance of Python, while offering a path researchers don't need to mess with C++.
I really want Mojo to take off. Maybe in a few years. The lack of an stdlib holds it back more than they think, and since their focus is narrow atm it's not useful for the vast majority of work.