I'm glad that it's open source now and they are supporting a lot more hardware. There are some interesting features that I hope the language design community pays attention to.
It's built on top of MLIR so you can make compiler optimizations in a library instead of the compiler. I believe Reactant.jl has been using MLIR for optimizing higher level abstractions in Julia. Imagine a Lisp with that capability.
Does this project have any meaningful traction? Seemed like a cool idea, but I wasn't even sure what problem does it solves. Looks like its completely missing from the regular discussion / news outlets. Every 1-2 years some barely visible post/article reminds me it even exists...
I think the compiler not being open-source hurt with getting people to check it out. Today, people are accustomed to most of it regarding PL development being out in the open, and Mojo was an outlier here.
> But I wasn't even sure what problem does it solves. Looks like its completely missing from the regular discussion / news outlets. Every 1-2 years some barely visible post/article reminds me it even exists...
At this point "developers" these days sound a lot more like consumers than those who actually do research on a tool that solves a problem. Ocaml is barely mentioned in the news and rarely HNers here use that language, but it is Jane Street that maintains and uses it.
Judging by hype isn't a great way of evaluating a language. I am not going to check the entire Nvidia stack, from CUDA, to CUTLASS to cuDNN and even on PyTorch's side just to solve a runtime error that could have originated from either place when Mojo solves all of that.
> At this point "developers" these days sound a lot more like consumers than those who actually do research on a tool that solves a problem.
No need for snarky comments. These days tools/frameworks/languages/libraries/etc are popping all the time. Do you expect people to research every simple signal they catch in the wild?
Maybe I'm a party pooper, but given Qualcomm history, open sourcing just after acquisition feels like they don't care about it and they're going to let it die while they cut Modular in pieces and extract all the juice possible of their cloud offering.
I had been holding off on testing out mojo till it was open sourced, and started picking it up this week.
So far I've been enjoying the language (pythonic, comptime, tile support) and plan to spend time using it to work with gpus to learn more, the puzzles are also pretty cool.
I'm pretty excited about mojo and look forward to it continuing into the phase of supporting systems programming. I have been using rust a lot lately for things I had used python for (that were not computation). I really like rust for static typing and functional programming patterns... but not for numerics. Hopefully mojo can become a serious staticly typed alternative to python.
When mojo 1.0 was announced, I looked into porting my current rust project (a very opinionated type-driven DICOM library/anonymizer that has a spec implemented in haskell) and it wasn't ready for that sort of work yet vs continuing with rust. Which is fine! The numerics side looks great. I'm glad they have reached 1.0 and open sourced.
This is nice, but the long time it took them to open source I think burnt a lot of the initial traction. I do like the idea & I'll see whether I can make use of it
I remember being really interested a few years ago when it was billed as a superset of Python. I know they pivoted away from that, but I might play with it now that the compiler is also open source.
Exciting. For hobby projects, I was looking into what should be my programming language. Open source was a criteria. Now I have choice between Rust and Mojo.
It's built on top of MLIR so you can make compiler optimizations in a library instead of the compiler. I believe Reactant.jl has been using MLIR for optimizing higher level abstractions in Julia. Imagine a Lisp with that capability.
At this point "developers" these days sound a lot more like consumers than those who actually do research on a tool that solves a problem. Ocaml is barely mentioned in the news and rarely HNers here use that language, but it is Jane Street that maintains and uses it.
Judging by hype isn't a great way of evaluating a language. I am not going to check the entire Nvidia stack, from CUDA, to CUTLASS to cuDNN and even on PyTorch's side just to solve a runtime error that could have originated from either place when Mojo solves all of that.
No need for snarky comments. These days tools/frameworks/languages/libraries/etc are popping all the time. Do you expect people to research every simple signal they catch in the wild?
This is by Chris Lattner, known for LLVM and Swift.
So far I've been enjoying the language (pythonic, comptime, tile support) and plan to spend time using it to work with gpus to learn more, the puzzles are also pretty cool.
https://youtu.be/eFbtGDGbdFU?si=VJ0XSiuNO9Z36DtD&t=30
When mojo 1.0 was announced, I looked into porting my current rust project (a very opinionated type-driven DICOM library/anonymizer that has a spec implemented in haskell) and it wasn't ready for that sort of work yet vs continuing with rust. Which is fine! The numerics side looks great. I'm glad they have reached 1.0 and open sourced.
Don't reward them with your support just because they are forced to open source something.
I do not see your point.
I remember being really interested a few years ago when it was billed as a superset of Python. I know they pivoted away from that, but I might play with it now that the compiler is also open source.
Strategically speaking, I think this only makes sense as an anti-NVIDIA play.