Breaking the scaling limits of analog computing
A new technique greatly reduces the error in an optical neural network, which uses light to process data instead of electrical signals. With their technique, the larger an optical neural network becomes, the lower the error in its computations. This could enable them to scale these devices up so they would be large enough for commercial uses.
Dirk Englund Ryan Hamerly Mach Zehnder Inferometers Saumil Bandyopadhyay Nature Communications Research Laboratory For Electronics
Source: mit.edu