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Not to distract from the awesomeness of this too much, but: what would it take to do the same type of thing but in Ruby? Being able to easily build rails apps a

• Exuma 4y ago
  Also wondering this
• josevalim 4y ago
  The amount of work varies because there are many different design decisions you can make. We have been working on this (Nx + Axon + Livebook + Bumblebee) for almost 2 years. One person full-time (part-time for the first year) and 3 part-time. But we have taken a foundational approach: instead of providing bindings to high-level libraries, we choose to build the whole foundation in Elixir and only leverage 3rd-party libraries at the compiler level. It looks like this: |-----------| | Bumblebee | pre-defined models |-----------| | Axon | NN library |-----------| | Nx | tensor library |-----------| | Compilers | |-----------| Everything is done in Elixir, except for the (pluggable) Compilers layer, which can be written in anything. The ones we use by default are from Google/Facebook and are written in C++. This design gives us agency and resiliency: we have control over how to evolve the whole stack and we can swap between different compilers depending how state of the art evolves. We are more expressive too, as we are not limited by design decisions done in libraries written in a separate language. But you can skip ahead provide direct bindings to libraries such as torch + torch.nn. This will cut corners but also will officially tie you to a Python library. However it is important to notice that embedding a neural network model inside your Phoenix app, as done in the video, is only really practical in a language that can fully leverage concurrency and effectively run both CPU/IO workflows in the same OS process. I am not following the progress of concurrent Ruby but my rough understanding is that it is not there. So in practice you would need to deploy your machine learning models to a separate service anyway. I hope this helps!