AI Infra2016
Provides a NumPy/SciPy-compatible GPU array library for Python, enabling existing NumPy/SciPy numerical code to run on NVIDIA CUDA and AMD ROCm with minimal changes. Exposes low-level CUDA features (RawKernels, Streams) and offers prebuilt binaries for multiple CUDA/ROCm versions.
AI Infra2018
Provides composable function transformations for Python+NumPy—automatic differentiation, JIT compilation, and vectorization—while using XLA to run and scale numerical programs on GPUs/TPUs for ML and scientific computing.