Automation has become part of the global manufacturing line, where robots take on repetitive jobs, like filling boxes or welding a car frame in the same way, day after day. But what if robots could step away from their limited range of tasks, and start to problem solve in complex operational situations, like spotting a malfunction on the assembly line or identifying a better compound for a part? And how could robots enabled with "deep learning" – where algorithms learn from large amounts of data collected via experience – begin to share insights with other robots, to increase innovation in all kinds of settings, from factories to self-driving cars on the road to early cancer detection and drug discovery in hospitals? These questions are the focus of Preferred Networks, a cutting-edge artificial intelligence company founded in 2014. The Tokyo-based firm, which is worth roughly $2 billion, according to CB Insights, is a symbol of Japan's sweeping strategic innovation initiative, where AI and robotics are viewed as keys to both solving social issues and achieving new economic growth.

How will humanity manage the growth of artificial intelligence systems? To answer that, French and Canadian officials are drafting a blueprint for an expert council that they hope could be a prototype for global cooperation on AI policy. The Global Partnership for AI (GPAI), advanced over the past year by French president Emmanuel Macron and Canadian prime minister Justin Trudeau, has started to take shape in a series of transatlantic negotiations in the past few months. While many details have yet to be resolved, negotiators hope for a general understanding by the end of this year, according to Malik Ghallab, director emeritus of a French state robotics lab in Toulouse, who is active in the planning process. The idea is to create a standing forum – involving government, industry and academia – to monitor and debate the policy implications of AI globally.