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The Challenges of Deploying Machine Learning Models in Python
There are a lot of challenges when it comes to deploying machine learning models in python. One of the challenges there is that python being single threaded that you have to actually run like eight replicas of this server to handle all of the load and it's not necessarily the easiest to maintain they're using kind of like an outdated version of space e which is a Python resource.
AI topics are all the rage right now, so we team up with Sean Moriarity to unpack what's going on and what it means for Elixir. Sean talks about Nx and his insights on the timing of Elixir's readiness for the public AI shift. He explains some of the Python frustrations that Elixir can alleviate and he shares tips on putting a PoC ML solution into a production Elixir app. Recently, Sean added LLaMa support to Bumblebee and he explains the background for the OpenSource Meta LLM people have been playing with and more! Turns out there's a lot to be excited about for AI and Elixir!
Show Notes online - http://podcast.thinkingelixir.com/154
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