A Collaborative Milestone in Photonic Research
Our team has successfully collaborated on a novel integrated photonic tensor processor capable of deep neural network inference, packaged in a standard 19-inch rack with a PyTorch interface. Read below to learn how Enlightra’s self-injection-locked microcomb technology is helping pave the way for scalable, ultra-high-speed optical AI accelerators.
We are proud to share that our team members have co-authored a groundbreaking paper now published in Nature Communications: "Deep neural network inference on an integrated, reconfigurable photonic tensor processor."
This research demonstrates a significant leap in how we can use light to accelerate AI. By performing neural network inference directly on an integrated photonic processor powered by Enlightra's microcomb technology, we are moving closer to a future of ultra-high-speed, energy-efficient computing.
A huge congratulations to our team, and our collaborators at Universität Heidelberg and Volkswagen for this achievement. This work underscores our commitment to pushing the boundaries of what’s possible with integrated photonics.
Read the full paper here: Deep neural network inference on an integrated, reconfigurable photonic tensor processor | Nature Communications