Indian student creates chip that can help phones respond faster to human commands

As the world increasingly embraces artificial intelligence, there is a growing demand for devices to process facial recogniition and respond faster to speech-to-text and human commands. This would involve either expensive infrastructure to support natural language processing (NLS) or machine learning on the device itself or bandwidth to send data to the cloud for decision-making. However, smaller devices do not have the power or infrastructure needed to run the data through complex neural networks - a mesh of information servers on which machine learning algorithms are trained - locally on the devices and hence have to send the data to the cloud, which increases response times. Now, an Indian-origin student at the Massachusetts Institute of Technology (MIT) in the US has developed a new processor chip that can speed up data processing on neutral networks by 3-7 times while reducing power consumption by 94-95%. This means that smaller devices such as smartphones or smart home appliances could run NLS or face recognition locally, and in turn, respond faster to human commands.