Meta has traditionally relied on using CPU-based servers for running AI workloads, but the increasing compute and memory requirements of these models have pushed the company towards using specialized solutions such as GPUs or other hardware accelerators. This talk describes the company’s effort in constructing its first silicon designed for its internal AI workloads and systems; It describes the accelerator architecture and platform design, and the software stack for enabling and optimizing workloads. It also touches upon the upcoming challenges and evolving requirements that need to be accommodated moving forward.