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AI Needs Enormous Computing Power. Could Light-Based Chips Help?
Optical neural networks, which use photons instead of electrons, have advantages over traditional systems. They also face major obstacles.
The development of optical computing is “paving the way for breakthroughs in fields that demand high-speed and high-efficiency processing, such as artificial intelligence,” said the University of Cambridge physicist Natalia Berloff. This approach to AI computation exploded in 2017, when a group led by Dirk Englund and Marin Soljačić of the Massachusetts Institute of Technology described how to make an optical neural network built on a silicon chip. To be clear, the system is still far from matching its electronic predecessors; HITOP performs about 1 trillion operations per second, whereas sophisticated Nvidia chips can chug through 300 times as much data, said Chen, who hopes to scale up the technology to make it more competitive.
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