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.

01:02:08

Creator website

Episode guests

Daniel Whitenack

José Valim

AI Chapters

Episode notes

Intro

2min

Elixir Meets Machine Learning

19min

Challenges and Optimizations in JAX and NX for GPU Computing

2min

Building Neural Networks with Axon and NX

3min

Navigating GPU Challenges and Elixir Integration

10min

Streamlining Software Development Through Abstraction and Familiar APIs

3min

Exploring Machine Learning in Elixir

21min

Exploring AI and Machine Learning Beyond Python

2min

This week Elixir creator José Valim joins Jerod and Practical AI’s Daniel Whitenack to discuss Numerical Elixir, his new project that’s bringing Elixir into the world of machine learning. We discuss why José chose this as his next direction, the team’s layered approach, influences and collaborators on this effort, and their awesome collaborative notebook project that’s built on Phoenix LiveView.

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Featuring:

José Valim – Website, GitHub, X
Jerod Santo – GitHub, LinkedIn, Mastodon, X
Daniel Whitenack – Website, GitHub, X

Show Notes:

Something missing or broken? PRs welcome!

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