“Meta is distinct in that there’s no wall between software use cases and hardware deployment — we’re developing custom silicon to support our own AI workloads. This allows us to get very specific in how we design our ASICs, which drives greater efficiency, and we can quickly deploy them into production workloads across Meta technologies, so we see the direct impact of our work.” As a custom silicon sourcing manager, Fangran X. helps procure critical components for MTIA — our family of custom-built silicon chips that support new generative AI products, services and advanced AI research. Head to the careers blog to learn why she thinks compute resources and cross-functional collaboration are key: https://lnkd.in/d82jVWxc #LifeAtMeta #MetaCareers #DataCenter #MTIA #CustomSilicon #AIinfra
This is an inevitable and necessary step towards end2end AI. As AI specific silicon become ubiquitous the need for and roll of legacy CPU technology will slip away. Even now CPUs as becoming the IO periphera of GPUs. At some point putting one foot in front of the other will no longer appear innovative; for now it still is.
Thanks for sharing. Interesting 💡
Helpful insight
A great example of how vertical integration linking custom silicon design directly with AI workloads can accelerate efficiency and innovation. Exciting to see how teams like this are shaping the future of generative AI infrastructure
Fully agree
Should do it
Love the collaboration Meta offers
World-Class Frontend Architect & Technical Writer | React • Next.js • TypeScript | Scalable Web Applications | Research & Technical Documentation Expert | Global Remote (USA/EU/Canada)
6dHelpful insight 💫💥