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a platform that would make distributed computing less of challenge would be well placed today with all the data science / ML / DL / AI focus but its not clear i

• zambal 3y ago
  As far as I know there are no Erlang projects with that ambition, but quite some interesting things are happening in the Elixir eco system: https://github.com/elixir-nx https://github.com/elixir-nx I'm a Elixir and Erlang developer who is just starting to explore ML, but these libraries seem solid and well designed.
• el_oni 3y ago
  I beleive there is currently a PhD project in collaboration with Jose Valim (Elixir's creator) which is looking at distributed machine learning. There is also the NX project (numerical elixir) which compiles tensors to GPU code making it much faster for those particular usecases. https://github.com/elixir-nx https://github.com/elixir-nx This has things like explorer which is elixir bindings to polars, livebook which is like jupyter notebooks (with enforced execution order thang god), aswell as some machine learning libraries in axon and scholar. There has also been some work with libraries like flow and broadway which allow pipelines to be constructed with the usual syntaxt `step1 |> step2 |> step3` but to be executed across cores (or cluster). I can imagine orgs using a combination of the above tools to do some interested distrubuted data pipelining and ML.