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Author: Admin | 2025-04-28
Olivia Wu, Meta’s Technical Lead for Infra Silicon, discusses the design and development of Meta’s first-generation AI inference accelerator. With the recent launches of MTIA v1, Meta’s first-generation AI inference accelerator, and Llama 2, the next generation of Meta’s publicly available large language model, it’s clear that Meta is focused on advancing AI for a more connected world. Fueling the success of these products are world-class infrastructure teams, including Meta’s custom AI silicon team, led by Olivia Wu, a leader in the silicon industry for 30 years.In the conversation below, Olivia 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.Tell us about your role at Meta.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 successfully build and deploy the silicon in our data centers.What led you to this role?OW: I’ve been working in the silicon industry for 30 years and have experience working at a variety of large companies leading both architecture and design for multiple ASICs and IPs, and for startups focused on training AI. In 2018, I saw a social media post from Yann LeCun, our Chief AI Scientist, that Meta was looking for someone to help build AI silicon in-house. I knew of just a few other companies designing their own custom AI silicon, but they were mainly focused only on silicon and not the software ecosystem and products. The opportunity for Meta (known as Facebook back then) was to bring in silicon developers to work directly with the software teams to reimagine end-to-end systems allowing for greater efficiency and larger degrees of freedom in optimizing across hardware and software boundaries. This was very enticing to me. I knew this was a rare opportunity and I had to jump on it to have the chance to build a design team from the ground up. How was the transition from working at two different startups to working at Meta?OW: My transition from startup to Meta was super easy. We had a very small team, so it
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