JAX Primitive

JAX primitives are custom functions integrated into the JAX ecosystem, a popular machine learning framework known for its automatic differentiation and just-in-time compilation capabilities. Current research focuses on extending JAX's functionality by creating primitives for diverse applications, including audio compression, spiking neural networks, unsupervised environment design, and computational fluid dynamics. This allows researchers to leverage JAX's strengths for efficient computation and gradient-based optimization in various scientific domains, accelerating research and enabling the development of novel algorithms and models. The resulting improvements in speed and ease of implementation are significantly impacting fields like deep learning, scientific computing, and high-performance computing.