Good news for Microsoft Band 2 owners who pair their wearable with an Android device: you're now getting one of the last big features that, until now, has been exclusive to Windows Phone. Microsoft has updated its Health app, in turn enabling Cortana on the Band 2 and allowing users to issue voice commands. This update makes the Band 2 work with Android in just about every single way it does with Microsoft's own Windows Phone platform. With Cortana on the Band 2, users can interact with the voice assistant without needing to touch their phone, getting notifications for messages and calendar events. All users need to do is speak into the wearable's mic.

The Pentagon has teamed up with DARPA and other agencies to create a "self-aware" AI, robot, that will use posts on social media to decipher a threat level of an individual and determine whether or not they should be placed on a kill list. It's called "Thrust", a new initiative from the Pentagon that will use predictive social media algorithms to determine when to use lethal force. Under Jade Helm 15, a new era began, the era of artificial intelligence and predictive technologies that "map the human domain". And now just a year later, this field is greatly expanding. Admitted in the document is the use of governmental shills, designed to infiltrate social media groups such as on Facebook, Twitter or Google, and then take an analysis of sorts.

Deep learning recently returned to the headlines when Google's AlphaGo program crushed Lee Sedol, one of the highest-ranking Go players in the word. Google has invested heavily in deep learning and AlphaGo is just their latest deep learning project to make the news. Google's search engine, voice recognition system and self-driving cars all rely heavily on deep learning. They've used deep learning networks to build a program that picks out an attractive still from a YouTube video to use as a thumbnail. Late last year Google announced Smart Reply, a deep learning network that writes short email responses for you.

Billionaire Tesla head Elon Musk recently told a tech conference in California that the chance is "one in billions" that we are not living in a simulated world. In other words, it's almost a certainty that we're all walking around in something akin to The Matrix -- a computer-generated reality run by artificial intelligence -- right this minute and the majority of us don't even realize it. He also said we should actually hope it is true because if it isn't, it means we're doomed to destruction by some other calamitous event. Musk is not the only person to suggest this. Science fiction writer Philip K. Dick told the Metz Sci-Fi Convention in France the same thing back in 1977: Dick said this explains the odd sense of déjà vu we all have from time-to-time.

While Musk's description of an injectable human-computer link may sound like science fiction, top tech executives repeatedly said that artificial intelligence (AI) was on the verge of changing everyday life, during discussion at a conference by online publication Recode this week. It is no secret that tech companies are diving into AI analytics research, an industry that will grow to 70 billion by 2020 from just 8.2 billion in 2013, according to a Bank of America report citing IDC research. AI, which combs through large troves of raw data to predict outcomes and recognize patterns, is already used in web search systems, marketing recommendation functions and security and financial trading programs. The technology will spread to driverless cars and service robots in the future, the Bank of America report said. Sundar Pichai, chief executive of Alphabet Inc's Google, said he sees a "huge opportunity" in AI.

There is a new technology being tested for use on UK civilians en masse on our streets, millimetre microwave scanners. These electromagnetic radiation scanners, which use Ultra Wide Band (UWB) at 75-110 GHz, are able to be beamed at crowds to detect potential concealed weapons being carried by individuals. Using the same technology as the American airport TSA scanners, over which there has been much controversy in the level of detail these scanners reveal about an individual, MiRTLE, provided by Radio Physics Solutions (RPS) purports to use artificial intelligence (AI) to identify weapon shaped objects without the system revealing the human body image. Practically this would make sense, as a human operator seeing a crowd of people imaged by'millimetre' microwaves would not be able to effectively scan the crowd for weapon shaped objects or suicide vests. Note that security workers, particularly those working at airports, have been drilled in various PR talking points in order to assuage public concerns on this experimental technology, including the popular corporate line that, "It's perfectly safe – it's on only millimeter microwaves."

Peter Norvig is a director of research at Google. Previously he was head of Google's core search algorithms group and of NASA Ames's Computational Sciences Division, making him NASA's senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He has taught at the University of Southern California and the University of California, Berkeley, from which he received a PhD in 1986 and the distinguished alumni award in 2006. He is coauthor of Artificial Intelligence: A Modern Approach, the leading textbook in the field.

In March this year, AlphaGo, a machine created by Google's artificial intelligence (AI) arm, DeepMind, trounced Mr Lee Sedol, a grandmaster at Go, the ancient Chinese game. AlphaGo used cutting-edge AI to beat a player acknowledged to be one of the greatest ever. For Go aficionados, the game will never be the same again, just as chess was changed when IBM's Deep Blue beat then world champion Garry Kasparov in 1997. That year, it was widely thought that while machines could master chess, beating the world's best at Go - a far more complex game with near-infinite variations of play - was still several decades away. Deep Blue used brute-force calculation and sheer computing power to beat the reigning world champion.

We'd be pleased to get feedback about how this book works out as a textbook, what is missing, or covered in too much detail, or what is simply wrong.

We introduce Bayesian Poisson Tucker decomposition (BPTD) for modeling country--country interaction event data. These data consist of interaction events of the form "country $i$ took action $a$ toward country $j$ at time $t$." BPTD discovers overlapping country--community memberships, including the number of latent communities. In addition, it discovers directed community--community interaction networks that are specific to "topics" of action types and temporal "regimes." We show that BPTD yields an efficient MCMC inference algorithm and achieves better predictive performance than related models. We also demonstrate that it discovers interpretable latent structure that agrees with our knowledge of international relations.