Introduction to Nx and its Implication for Elixir in Machine Learning

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Introduction to Nx and its Implication for Elixir in Machine Learning
José Valim announces the release of Nx (Numerical Elixir) v0.1, designed to bring Elixir to the realm of numerical computing and machine learning. Nx offers multi-dimensional arrays (tensors) and just-in-time compilation that work on both CPUs and GPUs. Valim provides an introduction to Nx, detailing its tensor operations, integration with backends like Torchx for optimized computations, and the use of defn for numerical definitions. The article explores various capabilities of Nx, including its use in machine learning through the Axon library. Valim also discusses the future directions for Nx, such as deeper integration with ONNX, incorporation of more compilers and backends, and the potential for distributed and federated learning. The post highlights the active efforts within the Elixir community to leverage the Erlang VM for new machine learning developments, ensuring that Nx remains a flexible and robust foundation for these advances.

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