Rice University engineers have developed a deep learning computer system that can accurately predict extreme weather events. Rice University engineers have developed a deep learning computer system that can accurately predict extreme weather events, like heatwaves, up to five days in advance using minimal information about current weather conditions. The new network uses an analog method of weather forecasting that computers made obsolete in the 1950s. The Phys.org website reported that the system was fed hundreds of maps that show surface temperatures and air pressures at five kilometers height, and each map shows those conditions several days apart. The new system is able to make five-day forecasts of extreme weather events like heat waves or winter storms with 85 percent accuracy, the German news agency reported.

A new photonic technology has enabled a computer system to mimic the way human brains learn from accumulating experience. Researchers from the Massachusetts Institute of Technology has developed a new approach for the deep learning computation using light, instead of electricity. A deep learning computer is a way computer system accumulate experiences and data and recognized the pattern in the accumulative data. Unfortunately, even the most powerful computer is limited with its transistor capacity to perform such function. In order to improve the deep learning computer system, researchers from the Massachusetts Institute of Technology discovered that light is a much better answer to perform such function, instead of electricity.