Jul 28, 2022

New hardware offers faster computation for artificial intelligence, with much less energy

Posted by in categories: health, robotics/AI

MIT researchers created protonic programmable resistors — building blocks of analog deep learning systems — that can process data 1 million times faster than synapses in the human brain. These ultrafast, low-energy resistors could enable analog deep learning systems that can train new and more powerful neural networks rapidly, which could be used for areas like self-driving cars, fraud detection, and health care.

Leave a reply