Machine learning is concerned with one aspect of this: given some AI problem that can be described in discrete terms (e.g. Typically some outside process is needed to judge whether the action was correct or not. In mathematical terms, it's a function: you feed in some input, and you want it to to produce the right output, so the whole problem is simply to build a model of this mathematical function in some automatic way. To draw a distinction with AI, if I can write a very clever program that has human-like behavior, it can be AI, but unless its parameters are automatically learned from data, it's not machine learning.

Much as Linux, Windows, and iOS coordinate the execution of computing applications, laws coordinate the execution of human society. When new kinds of interactions emerge – sharing our airspace with private drones, for example, or algorithmic trading on financial markets – new laws are encoded to regulate those activities. Laws respond to conflicts of interest, keep criminals and cheats in check, and temper the abuse of power. "Space law, tax law, online law, regulations for autonomous vehicles and artificial intelligence... if you think about laws and how they evolve to match the complexity of the functions they coordinate, laws become an interesting problem for complex systems science," says SFI President David Krakauer. During SFI's 2016 Applied Complexity Network (ACtioN) and Board of Trustees Symposium April 3-5, themed "Law OS," Krakauer announced the beginning of a new research program at SFI on "Complexity and the Law."

Recently, I needed to book a lunch meeting. To help coordinate, I asked Amy to assist and cc'd her on the email. "Amy," I wrote, "please help us find a time to meet. Let's plan for sushi at Tokyo Express on Spear Street." Amy looked at my calendar, found an open time suitable for everyone invited, and booked the meeting.

Global awareness of data privacy and its implications is improving, not least due to a spate of high profile image hacks. But this has been slow to translate directly into changed behaviour, as in many instances there has been no alternative to storing and archiving images other than on global online services, where data can be mined, hacked and shared. Pimloc, which intends to provide that alternative, was founded in March this year by serial entrepreneur Simon Randall. The founding team includes some of the world's foremost thinkers in deep learning visual technology and computer vision application development across a range of fields. The firm has already completed an oversubscribed seed funding round lead by staff and UK business angels.

SAP SE (NYSE: SAP) today introduced three initiatives to make its business applications more intelligent and empower its ecosystem to build machine learning (ML) applications for customers. Spanning its own solutions, partner programs and educational offerings, these programs will help accelerate ML adoption across SAP's global customer base. This announcement was made at the SAP TechEd conference, being held November 8-10, 2016, in Barcelona. First, SAP has unveiled new intelligent business applications. A new solution, "brand intelligence," is supposed to analyze brand exposure in video and images by leveraging deep learning.

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MR. NADELLA: I have tried to get much more focused on the sense of purpose and identity of Microsoft. We were a tools company. We were built for the hackers of the world, for the makers of the world, for the builders of the world. I have always felt that we are at our best when we express that identity with changing times. NADELLA: The most high-scale cloud service that Microsoft has is a Windows service, because we have one billion-plus PCs and devices, and they need to get serviced.

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"That would bother me a lot and it would bother others. "So yes, it can be used for bad outcomes. It's incumbent on us to make sure it's not concentrated in the hands of people who can implement this without checks and balances." Stephen Hawking, Nobel Prize winner and world-renowned physicist, also drew attention to the dark side of AI last month. For the moment artificial intelligence poses no immediate or obvious threat, but experts say it is a matter of time and work needs to be done now.