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Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

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Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#11
post #3

From a "marketing strategy" point of view, I wonder what the thinking is in investing in this stuff so heavily when Python seems to be kind of the go-to? Will they be able to create a "good enough" environment to do that kind of work with Elixir? Is it just someone or a company scratching their own itch? This is a genuine question - I don't know much about "AI stuff", but do know something about the economics of prog…

One factor may be that a few years back the language creator (José Valim, also the author of this article) announced that the language is basically "completed", and that they would shift focus to other things like developer tooling and other projects outside of the language itself. José is quite prolific, so I think it's natural that he moves on to things like this. It's hard to know what reception will be like until…

From a strictly "marketing" point of view, if you want to grow the language and ecosystem, it seems the successful move is to stake out a place where you're likely to win.

I think often this happens more or less by accident rather than conscious design - but think of something like PHP which made it really easy to whip up quick web pages, or Rails which drive Ruby adoption for a better, more structured, but still dynamic and quick web programming experience.

And I suppose part of those happy accidents are people just hacking on something they think is cool, so I wouldn't stress too much about the "marketing aspect". I'm just curious what drove it.

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#12
post #3

From a "marketing strategy" point of view, I wonder what the thinking is in investing in this stuff so heavily when Python seems to be kind of the go-to? Will they be able to create a "good enough" environment to do that kind of work with Elixir? Is it just someone or a company scratching their own itch? This is a genuine question - I don't know much about "AI stuff", but do know something about the economics of prog…

Jose may show up here and answer your questions... https://news.ycombinator.com/user?id=josevalim

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#13

People have to realise these are mostly for hobby. It is really hard to get these working with other libraries. Take explorer, it’s a mess trying to implement dplyr verbs in elixir. Anyone trying to use it is going to hit its limitations sooner or later. I tried migrating to it from polars but it is too frustrating.. gave up after some time. Why will people use half baked libraries instead of python ? I will stick to…

Explorer is still pre-1.0.

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#14
post #11

Earlier quoted context omitted.

One factor may be that a few years back the language creator (José Valim, also the author of this article) announced that the language is basically "completed", and that they would shift focus to other things like developer tooling and other projects outside of the language itself. José is quite prolific, so I think it's natural that he moves on to things like this. It's hard to know what reception will be like until…

From a strictly "marketing" point of view, if you want to grow the language and ecosystem, it seems the successful move is to stake out a place where you're likely to win. I think often this happens more or less by accident rather than conscious design - but think of something like PHP which made it really easy to whip up quick web pages, or Rails which drive Ruby adoption for a better, more structured, but still dyn…

My guess is that Jose and the core team are both personally interested in the big wave of ML stuff we've been experiencing recently and also want to demonstrate that Elixir is a viable platform for doing this work to teams which have adopted Elixir and are interested in ML but don't want to add a bunch of Python into their codebase.

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#15
post #3

From a "marketing strategy" point of view, I wonder what the thinking is in investing in this stuff so heavily when Python seems to be kind of the go-to? Will they be able to create a "good enough" environment to do that kind of work with Elixir? Is it just someone or a company scratching their own itch? This is a genuine question - I don't know much about "AI stuff", but do know something about the economics of prog…

I actually think the BEAM is an ideal environment for machine learning, sharding things across machines. The only thing I’m not sure of is if PyTorch etc. are more optimised than XLA the backend Axon uses… would be good to see some performance comparisons of a big LLM running on both. For everything else I’d suggest Elixir was a better experience.

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#16
post #14
post #11

Earlier quoted context omitted.

From a strictly "marketing" point of view, if you want to grow the language and ecosystem, it seems the successful move is to stake out a place where you're likely to win. I think often this happens more or less by accident rather than conscious design - but think of something like PHP which made it really easy to whip up quick web pages, or Rails which drive Ruby adoption for a better, more structured, but still dyn…

My guess is that Jose and the core team are both personally interested in the big wave of ML stuff we've been experiencing recently and also want to demonstrate that Elixir is a viable platform for doing this work to teams which have adopted Elixir and are interested in ML but don't want to add a bunch of Python into their codebase.

I would also guess that Elixir led to some crazy things they didn’t even imagine possible with web, like phoenixs live view [1]. Even if they don’t have explicit ideas of how it will impact ML, it’ll be really interesting to try.

[1]: https://phoenixframework.org/blog/phoenix-liveview-1.0-relea...

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#17
IMO the big win for Elixir/Nx/Bumblebee/etc is that you can do batched distributed inference out of the box without deploying anything separate to your app or hitting an API. Massive complexity reduction and you can more easily scale up or down. https://hexdocs.pm/nx/Nx.Serving.html#content

And there's also a scale to 0 story for when you're not using that GPU at all: https://github.com/phoenixframework/flame

1 language/toolchain. 1 deployable app. Real time and distributed machine learning baked in. 1 dev can go really far.

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#19
post #3

From a "marketing strategy" point of view, I wonder what the thinking is in investing in this stuff so heavily when Python seems to be kind of the go-to? Will they be able to create a "good enough" environment to do that kind of work with Elixir? Is it just someone or a company scratching their own itch? This is a genuine question - I don't know much about "AI stuff", but do know something about the economics of prog…

One factor may be that a few years back the language creator (José Valim, also the author of this article) announced that the language is basically "completed", and that they would shift focus to other things like developer tooling and other projects outside of the language itself. José is quite prolific, so I think it's natural that he moves on to things like this. It's hard to know what reception will be like until…

> a few years back the language creator announced that the language is basically "completed"

And then began adding an entire static type system to the language

Re: Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.

#20
post #3

From a "marketing strategy" point of view, I wonder what the thinking is in investing in this stuff so heavily when Python seems to be kind of the go-to? Will they be able to create a "good enough" environment to do that kind of work with Elixir? Is it just someone or a company scratching their own itch? This is a genuine question - I don't know much about "AI stuff", but do know something about the economics of prog…

We use Elixir for our primary application, with a fair amount of Python code to manage our ML pipelines. But we also need real-time inference and it's really convenient/performant to be able to just do that in-app. So I, for one, am very grateful for the work that's been done provide the level of tooling in Elixir. It has worked quite well for us.
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