Though hopefully it will be fully released open source still, but I feel there are question marks around whether it will be a priority to continue to develop by Qualcomm, or if they are mainly interested in the AI compute stack?

Time will tell I guess, but a lot feels to be up in the air.

To each their own!

You're right to ramble. I also believe that the world need a high level language fitting for accelerators that is not Python.

However developing something like that is by all means not a trivial task and many failed there.

"Mojo aims to combine the usability of a high-level programming language, specifically Python, with the performance of a system programming language such as C++, Rust, and Zig

Mojo builds on the Multi-Level Intermediate Representation (MLIR) compiler software framework, instead of directly on the lower level LLVM compiler framework like many languages such as Julia, Swift, C++, and Rust.[16][17]

MLIR is a newer compiler framework that allows Mojo to exploit higher level compiler passes unavailable in LLVM alone, and allows Mojo to compile down and target more than only central processing units (CPUs), including producing code that can run on graphics processing units (GPUs), Tensor Processing Units (TPUs), application-specific integrated circuits (ASICs) and other accelerators.

It can also often more effectively use certain types of CPU optimizations directly, like single instruction, multiple data (SIMD) with minor intervention by a developer, as occurs in many other languages"

https://en.wikipedia.org/wiki/Mojo_(programming_language)

The reason to move away from arm has nothing to do with performance, but rather avoiding licensing snafus like happened with their laptop chips. So far no one has delivered a risc-v core with class leading performance outside of the really low end. Not saying it can’t be done, but it will likely be a step back at first.

This is where an industry-spanning consortium would have helped out, but Mojo never really built those inroads with the hardware space. They just expected everyone else to opt-in to their mercurial middleware, which is a fundamental misunderstanding of how and why CUDA is successful.

I was really excited about it at launch, but its proprietary nature put me off.

I'm still not manage memory on GPU the way I would like, but mojo (or, my ignorant first stab at it) did not let me exploit direct DMA type things anyway.

It's now focusing on inferencing, both for data centers and edge. They already have an older AI100 NPU card and have other products in the pipeline including server class CPU that they are targeting for "Agentic" applications.

Don't ask what they will gain from owning it, ask what they will gain from others not owning it...

You're allowed to get a new job. Qualcomm is allowed to enter new markets.

There's actually a lot of ML deployed on phones. Both Google's and Apple's photo software uses it heavily for example.

> The industry standard is the NVIDIA Hopper H100/H200.

B200/B300/GB300 actually...

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.

> "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.