12 Other members of the JAX ecosystem

 

This chapter covers

  • Utility libraries, Libraries for LLMs, and other high-level neural network libraries for JAX
  • Libraries for other machine learning fields, including reinforcement learning and evolutionary computations
  • Other JAX modules for computer science, physics, chemistry, and more

By the JAX ecosystem, I mean a broad set of libraries, modules, and packages built on top of JAX or created to be interoperable with JAX or other ecosystem members.

The JAX ecosystem is vibrant and dynamic, with hundreds of modules dedicated to solving problems in diverse fields. As you know, JAX is great not only for deep learning but for the broader areas of machine learning, optimization, and other computer science fields.

There is growing adoption of JAX in other compute-intensive fields, like protein folding, chemical modeling, and especially physics, including molecular dynamics, fluid dynamics, rigid body simulation, quantum computing, astrophysics, ocean modeling, etc. New applications emerge constantly.

In this final chapter of the book, we look at the broader JAX ecosystem. We start with deep learning, then go to the wider fields of machine learning and computer science in general, and finish with physics and related fields.

12.1 Deep learning ecosystem

 

12.1.1 High-level neural network libraries

 
 

12.1.2 Large Language Models (LLMs) in JAX

 

12.1.3 Utility libraries

 
 

12.2 Machine learning modules

 

12.2.1 Reinforcement learning

 
 
 

12.2.2 Other machine learning libraries

 

12.3 JAX modules for other fields

 
 
 
 

12.4 Summary

 
 
 
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