Photonischer Prozessor könnte ultraschnelle KI-Berechnungen mit extremer Energieeffizienz ermöglichen

The deep neural network models that power today’s machine-learning applications have grown so large and complex that they are pushing the limits of traditional electronic computing hardware.

Photonic hardware, which can perform machine-learning computations with light, offers a faster and more energy-efficient alternative. However, there are some types of computations that a photonic device can’t perform, requiring the use of off-chip electronics that hamper speed and efficiency.

Building on a decade of research, scientists from MIT and elsewhere have developed a new photonic chip that overcomes these roadblocks. They demonstrated a fully integrated photonic processor that can perform all the key computations of a deep neural network optically on the chip.