Thursday, 28 July 2022

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

Researchers have created protonic programmable resistors -- the building blocks of analog deep learning systems -- that can process data 1 million times faster than the 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 then be used for novel applications in areas like self-driving cars, fraud detection, and health care.

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Engineers develop self-healing muscle for robots

Students recently unveiled their invention of a robotic actuator -- the 'muscle' that converts energy into a robot's physical mo...