As artificial intelligence (AI) becomes ubiquitous in fields such as medicine, education and security, there are significant ethical and technical challenges to overcome. While the credits to Star Wars drew to a close in a 1970s cinema, 10-year-old Cynthia Breazeal remained fixated on C-3PO, the anxious robot. "Typically, when you saw robots in science fiction, they were mindless, but in Star Wars they had rich personalities and could form friendships," says Breazeal, associate director of the Massachusetts Institute of Technology (MIT) Media Lab in Cambridge, Massachusetts. "I assumed these robots would never exist in my lifetime." A pioneer of social robotics and human–robot interaction, Breazeal has made a career of conceptualizing and building robots with personality.

A computer's victory over a human go master this past March reminds us of the pending "singularity" -- the rapidly approaching moment in time when artificial intelligence overtakes human intelligence. Machines will learn, and we won't be their teachers. Are we prepared for it? Can we prepare for it? Many futurists declare it inevitable, probably within a generation, maybe less.

Japan lags Silicon Valley in conventional internet services but could become a global leader in the deep-learning technology of artificial intelligence, a leading AI expert has said. Yutaka Matsuo, 41, Project Associate Professor at the University of Tokyo, believes machine learning will revolutionize sectors such as image recognition. "In deep learning, Japan still has a great chance to compete," Matsuo said in an interview. He singled out Sony Corp., Ricoh Co., Olympus Corp. and Canon Inc. as companies that show promise. "Changes happening now are in image processing technology, and Japan has been good at this," he said.

In winter, snowfall can rapidly disrupt daily life and impact on Japan's economy. Snowplowing is a considerable annual expense, and methods for co-ordinating plowing activity are needed to ensure an efficient, cost-effective service. Clever computer models are needed to manage such complex activities, which involve many agents and interactions. Now, Satoshi Takahashi at the University of Electro-Communications, and Tokuro Matsuo at the Advanced Institute for Industrial Technology in Tokyo have devised a computational method that combines task allocation and scheduling of individual snow-plows to maximize efficiency. The researchers aimed to identify the best routes for multiple snow-plows to take without replicating route paths, meaning their computer model had to allocate and schedule tasks simultaneously.