Tbh, Modular getting acquired happened sooner than I would have expected, if ever. Don't know how to feel about this one.
Also so many mixed feelings about Mojo, the programming language powering Modular. Of course Chris Lattner is free to pursue whatever he wants, his many contributions to tech will always be highly regarded, but to me it feels as if he "wasted" lots of his precious mental capacity on making Mojo a python-like language instead of trying to come up with something better from first principles. I know, the promise of Mojo eventually being a Python superset has been taken back, which I think is the right move, and I understand why Mojo's initial motivation for being close to Python was to attract ML folks, but I'm getting counterfactual regret just by thinking about what Chris Lattner could have achieved by making a new programming language truly from scratch and not letting some undesireable pythonisms muddy the language.
Anyway, sorry for rambling. Congrats to the team at Modular!
> 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.
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"
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'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.