Modular Raises $100M
modular.com
modular.com
So my question for users is - what can you actually do in this better than PyTorch or numpy? Interested in exploring it if there is anything worth bothering with.
For example, do they present any problems with highly optimised numpy/torch solutions and show how modular does it better?
We are also excited to announce the next major step forward for Mojo – the ability to download Mojo and a whole developer toolset locally to your desktop machine. The ability to run Mojo locally is the most requested feature from Mojo developers so far and will lead to increased innovation and collaboration in the Mojo developer ecosystem. We are shipping a preview of the Mojo SDK to hundreds of early adopters today, and we will release it generally to everyone in early September. Sign up to download [0].
> Looking ahead, we are committed to releasing the Mojo standard library in open source and accepting contributions before the end of the year.
that doesn't say compiler or tooling, just standard library.
Anyway, I found the FAQ section and the relevant bits
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Will Mojo be open-sourced?
Yes, we expect that Mojo will be open-sourced. However, Mojo is still young, so we will continue to incubate it within Modular until more of its internal architecture is fleshed out. We don’t have an established plan for open-sourcing yet. Why not develop Mojo in the open from the beginning?
Why not develop Mojo in the open from the beginning?
Mojo is a big project and has several architectural differences from previous languages. We believe a tight-knit group of engineers with a common vision can move faster than a community effort. This development approach is also well-established from other projects that are now open source (such as LLVM, Clang, Swift, MLIR, etc.).
What? Pretty sure you don’t have 20K enterprise customers.
The promise of the engine is the same as Lattner’s LLVM was for compilers: train on the back end of your choice, and run it on the front end of your choice. It is modular.
That breaks the hardware-software link.
https://www.modular.com/engine
Scroll down to the first flow chart. Note how they stuck Nvidia over to the bottom-right. That was intentional. ARM, the cheapest data center CPU hardware and the most prevalent at the edge, is in the middle. They launched with CPU support first, now doing GPUs.
The main dividing line in LLMs and other large models is becoming giant commercial models running on GPU cloud vs open source at the edge or CPU cloud.