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I'm actually mostly worried about the future of Mojo at this time.

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.

Looked up Mojo

"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)

> sorry for rambling.

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.

He already did that, Swift for Tensorflow, the project hardly survived one year after the public announcement.

To say nothing of "Swift for TensorFlow" when Julialang was an option.

To each their own!

"first principles" and "from scratch" are predictable failure modes... he had very good reason to pursue a Python-like language given the circumstances and objectives

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.

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.

The best cross-platform API is CUDA, because we have ROCm.

> Moving beyond ARM to RISC-V

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.

Whats peoples thoughts on Tenstorrent - they were looking for funding on Hiive recently but that deal got pulled when Qualcomm rumours surface a week or so ago.

Could be the reason that Qualcomm decided to buy them out. Hire someone who knows how to fix the problem.

Patents, and tooling portfolio.

I call BS, zero chance this traded at $4B. The fact they describe it as a "chip company" shouldn't give confidence

It's the first sentence of the article? "an all-stock deal valued at nearly $4 billion"

> I don't get it. > > Qualcomm has almost no products in the high-end inference/training market. The industry standard is the NVIDIA Hopper H100/H200. > > What could they possibly get from acquiring Modular?

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

> Qualcomm has almost no products in the high-end inference/training market.

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...

Qualcomm is pivoting.

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.

Are the Qualcomm Dragonfly chips not considered high end?

> I don't get it. Qualcomm has almost no products in the high-end inference/training market

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

You've never heard of an acquihire?

Mojo seemed like a passion project. The fundamental problem was never the lack of a great programming language, and inventing a python bastard child of a language is not a solution. But, respect and congrats to the Modular folks. HW companies have notoriously bad software teams and culture and hopefully this injects some good sw dna into the acquirer.

Are you a bot?

I have a friend who is doing stuff with it, and he's incredibly excited about it, which is definitely a good sign.

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

I tried, also all a little while ago, really found the puzzles fun to do and then tried to implement some basic radar pipeline things and found lots of just basic 'building blocks' for signal processing (i/o things, fft) were missing to the point I went back to JAX.

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.

Why you say that? Nuvia made a massively great success with Oryon CPUs which are now all over the place.

Nvidia wasn't going to buy them. Unless Mojo intended to compete toe-to-toe in the hardware space, they were destined to get bought out by a hardware underdog at some point or another.

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.

It's on the front page now.

There are multiple HN submissions on this topic and none of them gets traction. Weird...