Machine learning models currently require extensive computational resources and this demand is growing rapidly with new models and applications being introduced.
Engineers in Prof. Shanhui Fan's laboratory have developed an efficient, scalable, in-situ method to train, configure and tune complex photonic circuits for artificial intelligence and machine learning.
Stanford researchers at the Fan Group have designed and tested a highly efficient radiative cooler prototype with the following record-breaking performance results: