photonic-computing
(4)
Neurophos
Neurophos is an Austin-based photonics startup building an Optical Processing Unit (OPU) that uses light instead of electrons to run AI inference. Spun out of Duke University and the Metacept incubator, the company packs more than a million micron-scale metamaterial optical modulators - roughly 10,000x smaller than conventional photonic elements - onto a single chip to perform the matrix-vector multiplication at the heart of large AI models. It positions the OPU as an energy-efficient, drop-in alternative to GPUs for data-center inference, and raised a $110M Series A led by Gates Frontier in January 2026.
Opticore
Opticore is a photonic computing startup building optical processing units (OPUs) - chips that run AI workloads with light and waveguides instead of electrons. Spun out of research at MIT, USC and UC Berkeley, the company claims its photonic chips are up to 100x more energy efficient and offer roughly 25x the computing density of leading GPUs, using time-multiplexed computing to encode as many as a trillion parameters on a single chip. Opticore has raised about $14.5M to date to attack the energy and 'memory wall' bottlenecks of AI data centers.
Arago
Arago is a Paris and Palo Alto deeptech startup building a photonic AI accelerator that uses light instead of electrons to run AI workloads, targeting 10x lower energy consumption than today's leading GPUs at equivalent performance and cost while staying compatible with PyTorch and standard hardware ecosystems.
Lightelligence
Lightelligence builds photonic and optoelectronic hybrid computing hardware that moves and processes AI data with light instead of electrons. Spun out of MIT in 2017 on the back of a landmark Nature Photonics paper, the company designs silicon-photonics chips, optical interconnects, and AI accelerators aimed at the bandwidth and energy bottlenecks of modern data centers. In April 2026 it listed in Hong Kong as the world's first AI silicon-photonics chip stock, jumping roughly 400% on debut.