Modular now joins SYCL, OpenCL, and One API on the list of cross platform languages which never really became cross platform.
After so long and so much investment in AI, the best cross-platorm API we've got for high performance Kernels is vulcan, a graphics API. That is sad.
Still, this is pretty good for Modular's employees, probably good for Qualcomm. It's just terribly disappointing for anyone who invested time learning mojo in the hope it might actually become cross platform.
I might be reading this differently, but isn't the acquisition a bet that Modular will become a manufacturer-agnostic software stack?
> "We believe the future belongs to developer-friendly, horizontal platforms that can run across diverse compute environments and give customers real choice in how and where they deploy AI," Qualcomm CEO Cristiano Amon said.
I also believe this. And I think very few people can pull it off, and Chris Latt ner is precisely one of them. I hope that the agreement includes open sourcing Mojo at some point. Chris mentioned fall 2026, iirc.
one of the reasons I rarely read press releases is that I don't believe in promises -- I believe in _incentives_. In this case, what will Qualcomm be incentivized to do? What are in their interests?
Ok, what will be Qualcomm incentive? Selling few hundred Mojo license for few thousand dollars each. Or making it open source hoping it may make big in AI / data science community and may help sell more Qualcomm hardware?
Qualcomm has an enormous incentive in breaking Nvidia's CUDA grip on GPU programming.
Having Mojo support multiple platforms creates incentive to adopt Mojo and therefore write code in a language which can compile and run on Qualcomm hardware. This is good for Qualcomm.
However the danger is that the language sees wide adoption but nobody uses it with Qualcomm hardware. Instead it might encourage people to buy AMD. This is a terrible outcome for Qualcomm. They paid to boost someone else's sales.
So the incentive is to make sure it runs best on Qualcomm and to at least slightly hobble other hardware. But the safest thing overall is to support Nvidia, Qualcomm, and that's it.
The competition to CUDA and proprietary 3D APIs always overlooks developer productivity.
For some strange reason there is this expectation, maybe due to UNIX background of those folks, that portable APIs have to exist without good IDE tooling, no graphical debuggers, no high level programming models, no libraries ecosystem.
Then for some "strange" reason, GPU developers mostly pick proprietary and the cycle repeats itself.
But the Modular stack is focused on developer productivity. It is still early but there has been substantial work on all these
I am yet to see the same Windows love as CUDA.
Same to IDE integration and graphical debugging experience for GPU code.
Until now, it was been the usual UNIX cli, and text mode lldb like debugging for CPU side.
At least it what I have been made aware of.
It doesn't have a lot of Windows support yet because nobody deploys datacenter-scale AI serving on Windows OS.
The best cross-platform API is CUDA, because we have ROCm.
Only superficially, given what CUDA provides and what ROCm supports.