JAX is an open-source library for hardware-accelerated scientific computing on GPUs, TPUs, and CPUs. This talk will serve as an introduction to the powerful collection of paradigms, including batteries-included automatic differentiation, adopted by JAX that allows us to write extremely performant code in ordinary Python that executes on hundreds or thousands of accelerators for building the largest machine learning models on the planet.

*This kick-off event will be happening at Google for Korea 2025. 내부 초대로만 진행되는 Google for Korea 2025 행사의 사이드 트랙으로 진행됩니다.

*Internal Invitation Only, 이메일로 초대 받으신 분들만 신청 가능합니다.