MIT AI Hardware Program

Deep Learning with Light

Adam Zewe | MIT News Office

A new novel piece of hardware, called a smart transceiver, uses silicon photonics to accelerate machine-learning computations on smart speakers and other low-power connected devices.

rendering of a novel piece of hardware, called a smart transceiver, that uses silicon photonics to dramatically accelerate running a machine-learning model

Adam Zewe | MIT News Office
October 20, 2022

Ask a smart home device for the weather forecast, and it takes several seconds for the device to respond. One reason this latency occurs is because connected devices don’t have enough memory or power to store and run the enormous machine-learning models needed for the device to understand what a user is asking of it. The model is stored in a data center that may be hundreds of miles away, where the answer is computed and sent to the device.

MIT researchers have created a new method for computing directly on these devices, which drastically reduces this latency. Their technique shifts the memory-intensive steps of running a machine-learning model to a central server where components of the model are encoded onto light waves.

Complete article from MIT News.

Explore

Privacy Preference Center

Privacy Preferences