The Changelog: Software Development, Open Source Elixir meets machine learning (Interview)
May 7, 2021
José Valim, the creator of Elixir, teams up with Daniel Whitenack, co-host of the Practical AI podcast, to dive into the innovative Numerical Elixir project. They explore how Elixir merges with machine learning, showcasing a live demo of building a neural network classifier. The duo discusses the challenges of GPU integration, the evolution of Elixir for AI, and the user-friendly Axon framework. Their insights highlight a vibrant community and encourage developers to explore the exciting potential of machine learning beyond Python.
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Project Origin
- José Valim's interest in machine learning was reignited by a book on genetic algorithms for Elixir.
- This led him to connect with Sean Moriarty, an AI expert in the Elixir community, and start the NX project.
Immutability as a Feature
- Elixir's immutability, initially considered a drawback for numerical computing, became a strength.
- The JAX library in Python, also immutable, inspired the Numerical Elixir (NX) project.
Avoiding Pitfalls
- JAX in Python uses the "tape pattern," which has some pitfalls due to mutability.
- NX in Elixir avoids these pitfalls because of its inherent immutability and use of macros.
