Show me I can save a considerable amount of time training a 70b parameter huggingface model by switching to Elixir, then we can talk about me learning a new language.
The training costs and performance at that scale are mostly driven by hardware and I personally don't think language will make a large difference (I may be wrong).
Most of the Elixir Nx efforts are on inference, especially on how you can embed and scale it using concurrent and distributed patterns (see this post/video [1]). It may not be what you are looking for but we have more folks deploying than training models, so maybe they will find incentives to give Elixir a try. :)
Seems like you didn't read even the first line as this article is directed at people already using Elixir who are currently doing ML stuff with Python.
Most of the Elixir Nx efforts are on inference, especially on how you can embed and scale it using concurrent and distributed patterns (see this post/video [1]). It may not be what you are looking for but we have more folks deploying than training models, so maybe they will find incentives to give Elixir a try. :)
[1]: https://news.livebook.dev/distributed2-machine-learning-note...