Engineers Build Reconfigurable Artificial Intelligence Chip - Tech Briefs

Massachusetts Institute of Technology, Cambridge, MA

MIT engineers have created a reconfigurable AI chip that comprises alternating layers of sensing and processing elements that can communicate with each other. (Image: Figure courtesy of the researchers and edited by MIT News)

MIT engineers are taking a modular approach with a LEGO-like design for a stackable, reconfigurable artificial intelligence chip. The design comprises alternating layers of sensing and processing elements, along with light-emitting diodes (LED) that allow for the chip’s layers to communicate optically. Other modular chip designs employ conventional wiring to relay signals between layers. Such intricate connections are difficult if not impossible to sever and rewire, making such stackable designs not reconfigurable.

The MIT design uses light, rather than physical wires, to transmit information through the chip. The chip can therefore be reconfigured, with layers that can be swapped out or stacked on, for instance to add new sensors or updated processors.

“You can add as many computing layers and sensors as you want, such as for light, pressure, and even smell,” said MIT Postdoc Jihoon Kang. “We call this a LEGO-like reconfigurable AI chip because it has unlimited expandability depending on the combination of layers.”

“As we enter the era of the internet of things based on sensor networks, demand for multifunctioning edge-computing devices will expand dramatically,” said Jeehwan Kim, Associate Professor of Mechanical Engineering at MIT. “Our proposed hardware architecture will provide high versatility of edge computing in the future.”

The team’s design is currently configured to carry out basic image-recognition tasks. It does so via a layering of image sensors, LEDs, and processors made from artificial synapses — arrays of memory resistors, or “memristors,” that the team previously developed, which together function as a physical neural network, or “brain-on-a-chip.” Each array can be trained to process and classify signals directly on a chip, without the need for external software or an internet connection.

The researchers are eager to apply the design to edge computing devices — self-sufficient sensors and other electronics that work independently from any central or distributed resources such as supercomputers or cloud-based computing.

For more information, contact Abby Abazorius at 617-253-2709 or abbya@mit.edu.