Key Points
It holds that computer chips pack in twice as many transistors every two years or so, producing major jumps in speed and efficiency..
Zaijun Chen, a former MIT postdoc now based at the University of Southern California, said this helps HITOP overcome one of the drawbacks of optical neural networks: It takes significant energy to transfer data from electronic components into optical ones, and vice versa..
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..
While optical computing has advanced quickly over the past several years, its still far from displacing the electronic chips that run neural networks outside of labs..
Last year his groupran simulations showing that, within a decade, a sufficiently large optical system could make some AI models more than 1,000 times as efficient as future electronic systems..
