7 ms·

For a language that announced itself (and raised a lot of money on the premise of) claiming to be "a Python superset", this does not sound like a huge achieveme

• boxed 1y ago
  I believe they're still working towards making the syntax and semantics more python-like.
• dragonwriter 1y ago
  The real unique selling point of Mojo is "CPU+GPU execution without CUDA", specifically, you write code that looks like code without worrying about distinctions like kernels and device functions and different ways of writing code that runs on GPU vs. code that runs on CPU, and mojo compiles it to those things.
  • eigenspace 1y ago
    Not unique though. Julia has had that since before Mojo was even started.
    • melodyogonna 1y ago
      What does the performance of Julia's GPU kernels look like in comparison to kernels written by Nvidia or AMD?
      • ChrisRackauckas 1y ago
        Benchmarks of an early version on NVIDIA's blog show that it is about the same (the average across the benchmark shows Julia as actually a little faster here, but it's basically a wash) https://developer.nvidia.com/blog/gpu-computing-julia-programming-language/ https://developer.nvidia.com/blog/gpu-computing-julia-progra.... While much has changed since then, the architecture is effectively the same. Julia's native CUDA support simply boils down to compiling via the LLVM .ptx backend (Julia always generates LLVM IR, and the CUDA infrastructure "simply" retargets LLVM to .ptx, generates the binary, and then wraps that binary into a function which Julia calls), so it's really just a matter of the performance difference between the code generated by the LLVM .ptx backend vs the NVCC compiler.
• Certhas 1y ago
  I think it was pretty clear immediately that running python code was a far away goal. There was a lot more talk about lifetimes and ownership semantics than details about Python interop. Mojo is more like: Can we take the learnings of Swift and Rust and solve the usability and compile time issues, while building on MLIR to target arbitrary architectures efficiently (and call it a Python superset to raise VC money). That said, the upside is huge. If they can get to a point where Python programmers that need to add speed learn Mojo, because it feels more familiar and interops more easily, rather than C/CPP that would be huge. And it's a much lower bar than superset of python.
  • amval 1y ago
    It marketed itself explicitly as a "Python superset", which could allow Python programmers to avoid learning a second language and write performant code. I'd argue that I am not sure what kind of Python programmer is capable of learning things like comptime, borrow checking, generics but would struggle with different looking syntax. So to me this seemed like a deliberate misrepresentation of the actual challenges to generate hype and marketing. Which fair enough, I suppose this is how things work. But it should be _fair_ to point out the obvious too.
    • fnands 1y ago
      They've backed off a little from the Python superset claims and leaned more into "Python family". > I'd argue that I am not sure what kind of Python programmer is capable of learning things like comptime, borrow checking One who previously wrote compiled languages ;-). It's not like you forget everything you know once you touch Python.
      • oxidi 1y ago
        I think the point was that Python syntax is simpler than e.g. borrow checking. Although Python has some seriously PERLesque YOLO moments, like "#"*3 == "###". This is admittedly useful, but funny nonetheless.
        • 1y ago
• dismalaf 1y ago
  It was never going to have Python semantics and be fast. Python isn't slow because of a lack of effort or money, it's slow because of all the things happening in the interpreter.
• saghm 1y ago
  > For a language that announced itself (and raised a lot of money on the premise of) claiming to be "a Python superset", this does not sound like a huge achievement I feel like that depends quite a lot on what exactly is in the non-subset part of the language. Being able to use a library from the superset in the subset requires being able to translate the features into something that can run in the subset, so if the superset is doing a lot of interesting things at runtime, that isn't necessarily going to be trivial. (I have no idea exactly what features Mojo provides beyond what's already in Python, so maybe it's not much of an achievement in this case, but my point is that this has less to do with just being a superset but about what exactly the extra stuff is, so I'm not sure I buy the argument that the marketing you mention of enough to conclude that this isn't much of an achievement.)
• melodyogonna 1y ago
  I've written this somewhere else before, Modular did not raise $130m to build a programming language, nobody does that. They raised that much money to revolutionize AI infrastructure, of which a language is just a subset. You should definitely check some of the things they've put together, they're amazing
  • Imustaskforhelp 1y ago
    Yes. They are revolutionizing AI infrastructure but I guess a lot of world is just babbling about AI, but not every developer needs to worry about AI. And so his improvements in mojo and now calling mojo code from python just make a lot more net positive to the community than being, some other Ai infrastructure company. So I do wish a lot of good luck to mojo. I have heard that mojo isn't open source but it has plans to do so. I'd like to try it once if its as fast / even a little slower than rust and comparable to understanding as python.
    • melodyogonna 1y ago
      I don't think investors look at what makes a net positive to the community when making large investments like in Modular. I was calling out the part of the post that said Modular raised a lot of Money to develop Mojo, that isn't entirely true as just creating a language isn't enough reason to invest $130m into a company, no matter how much net-positivity the language would bring.
    • ModernMech 1y ago
      Agreed, Modular is walking a very fine line, and they're doing so by trading on the reputation of Chris Lattner. On the one had, as the other poster noted, no one raises $100M+ for a programming language; programming languages have no ROI that would justify that kind of money. So to get it, they had to tell VCs a story about how they're going to revolutionize AI. It can't just be "python superset with MLIR". That's not a $100M story. On the other hand, they need to appeal to the dev community. For devs, they want open source, they want integration with their tools, they don't want to be locked into a IP-encumbered ecosystem that tries to lock them in. That's where the tension is. To raise money you need to pretend you're the next Oracle, but to get dev buy-in you have to promise you're not the next Oracle. So the line they've decided to walk is "We will be closed for now while figure out the tech. Then later once we have money coming in to make the VCs happy, we can try to make good on our promise to be open." That last part is the thing people are having trouble believing. Because the story always goes: "While we had the best intentions to be open and free, that ultimately came secondary to our investors' goal of making money. Because our continued existence depends on more money, we have decided to abandon our goal of being open and free." And that's what makes these VC-funded language plays so fraught for devs. Spend the time to learn this thing which may never even live up to its promises? Most people won't, and I think the Darklang group found that out pretty decisively.
• meander_water 1y ago
  Fwiw the website still claims this: > Further, we decided that the right long-term goal for Mojo is to adopt the syntax of Python (that is, to make Mojo compatible with existing Python programs) and to embrace the CPython implementation for long-tail ecosystem support Which I don't think has changed.