View Olivia Wu’s profile on LinkedIn, a professional community of 1 billion members. Experience: Meta · Location: San Francisco Bay Area · 500+ connections on LinkedIn.

2023年10月18日 · Olivia Wu: I lead design development of the next generation of Meta’s AI silicon. My team is responsible for the design and development of Meta’s in-house machine learning (ML) accelerator, and I partner closely with our co-design, architecture, verification, implementation, emulation, validation, system, firmware, and software teams to ...

Meta's Olivia Wu, Technical Lead for Infra Silicon, explains how she led the silicon design team to deliver Meta’s AI silicon, allowing the company to improve the compute efficiency of the infrastructure, and enable software developers to create AI models that will provide more relevant content and better user experiences.

2023年10月23日 · Central to these advancements is Olivia Wu, Meta's Technical Lead for Infra Silicon. With 30 years of unparalleled expertise in the silicon domain, Olivia is pioneering Meta's AI silicon...

Olivia Wu, Meta’s Technical Lead for Infra Silicon, discusses the design and development of Meta’s first-generation AI inference accelerator and driving a team of silicon developers to build cutting-edge designs for AI hardware. Learn more about her career journey https://meta.careers/49c2GSV#CustomSilicon#AIInfra#AIHardware#WomenInTech.

I'm absolutely thrilled to share the launch of Next Gen MTIA, Meta's second generation training and inference accelerator customized for Meta's AI workload. It is a tremendous team effort to bring...

2023年10月18日 · Olivia Wu, Meta’s Technical Lead for Infra Silicon, discusses the design and development of Meta’s first-generation AI inference accelerator and driving a team of silicon developers to build...

Meta has traditionally relied on using CPU-based servers for running inference workloads, specifically Deep Learning Recommendation Models (DLRM), 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.