Krystian Woznicki (KW):'Rethinking political agency in an AI-driven world' is the topic of the AMBIENT REVOLTS conference in Berlin on 8–10 November. I would therefore like to begin by asking you about the deployment of algorithms at state borders. You have noted that'in order to learn, to change daily and evolve [they] require precisely the circulations and mobilities that pass through'. This observation is part of your larger argument about how governmentality is less concerned with prohibiting movement than with facilitating it in productive ways. The role of self-learning algorithms would seem to be very significant in this context, since – like capitalism – they also hinge upon movement. When it comes to their thirst for traffic, how do you think that relationship between self-learning algorithms and capitalism? Louise Amoore (LA): Yes, I agree that the role of'self learning' or semi-supervised algorithms is of the utmost relevance in understanding how movement and circulation matters.

Artificial intelligence (AI) that reasons like a human remains elusive, but Honda hopes to make inroads. The Tokyo company's U.S.-based Research Institute today announced a collaboration with three academic institutions -- the Massachusetts Institute of Technology (MIT), the University of Pennsylvania (Penn), and the University of Washington -- to advance the field of artificial cognition. MIT's Computer Science and Artificial Intelligence (CSAIL) lab, in partnership with Penn's School of Engineering and Applied Science and the University of Washington's Paul G. Allen School of Computer Science & Engineering, will develop prototypes, working examples, and demonstrations of what Honda calls the "mechanisms of curiosity." Specifically, MIT CSAIL will focus its efforts on systems capable of predicting future percepts -- concepts developed as a consequence of perception -- and the effect of future actions, while Penn's engineering department and the Paul G. Allen School will develop perception models informed by biology and robots that can work safely in human environments. Grants will fund the first leg of research.

Defense Specialist Allison Barrie has the latest information on micro-bots and milli-bots, the next generation of drones that will be smarter, faster and deployable in powerful swarms. In future battles, new American warriors may be the size of a baseball, the size of a bumble bee – even the size of a grain of sand. Micro-bots and milli-bots may be small in size, but they are giant in terms of impact. This next generation of drones will also be smarter, faster and deployable in powerful swarms. The futuristic intelligence on these machines is mind-boggling and will make current "autonomy" look positively prehistoric.

Whenever an earthquake strikes, news reports quickly fill in certain details, such as how strong the quake was and where it was centered. That information comes from a networks of seismometers scattered across the planet. Seismometers, though, can be expensive to install and maintain over long periods, and researchers cannot place them everywhere they might like, such as in the densely built and expensive streets of an earthquake-prone city like San Francisco. Some scientists, however, are exploring a different approach, using a sensor that is already widely deployed beneath the streets of towns and cities around the world. That sensor is the common fiber-optic cable, used to carry telephone and Internet traffic.

Artificial Intelligence (AI) systems are taking over a vast array of tasks that previously depended on human expertise and judgment. Often, however, the "reasoning" behind their actions is unclear, and can produce surprising errors or reinforce biased processes. One way to address this issue is to make AI "explainable" to humans--for example, designers who can improve it or let users better know when to trust it. Although the best styles of explanation for different purposes are still being studied, they will profoundly shape how future AI is used. Some explainable AI, or XAI, has long been familiar, as part of online recommender systems: book purchasers or movie viewers see suggestions for additional selections described as having certain similar attributes, or being chosen by similar users.

History is rife with fakes. In 1983, the German magazine Stern announced that it had acquired previously undocumented diaries written by Hitler, a find British historian Hugh Trevor-Roper initially heralded as "an archive of great historical significance." In reality, however, an illustrator named Konrad Kujau had penned the volumes himself. Thanks to the scrutiny of historians at the German Federal Archive, they were soon revealed to be forgeries and the so-called "Hitler Diaries" became a cautionary tale about media frenzies. Imagine, however, if experts couldn't readily identify the diaries as fraudulent.

Donald Trump has complained that fewer people are following him on Twitter, accusing the site of undermining him. Amid a series of unfolding crises, the president took to his Twitter account to complain that he had lost followers. He also appeared to suggest that the site is making it harder to follow him, for which there is no evidence. "Twitter has removed many people from my account and, more importantly, they have seemingly done something that makes it much harder to join - they have stifled growth to a point where it is obvious to all," he posted. "A few weeks ago it was a Rocket Ship, now it is a Blimp!

By Jackie Snow Judging by the breathless coverage, it can seem as if the only countries developing artificial intelligence are the United States and China. But while companies in those two countries are leading the way in cutting-edge research and products, it's still early for the industry and other nations are working hard to become major AI players. Here are six that could challenge the two juggernauts. SINGAPORE Singapore was one of the first countries to announce a national strategy, called AI Singapore, in May 2017. The initiative brings the government, research institutions and companies together to collaborate on research and speed up local adoption of AI, with $109 million to spend over five years.

From my Northern Irish vantage point, I coordinate and facilitate a collaborative network around AI. Our 30 members range from micro SMEs through to multinational organisations, such as Liberty IT and Allstate. As such, I am privy to an incredible range of AI based applications and solutions that are coming down the line, and I am always surprised at the pace of change in the industry. With every change, we need to take a few steps back and rethink how to frame the state of the art at that given time – so it's worth keeping in mind that what is state of the art at any given time may well be seen as mundane in just a few short months. For example, when the age of the AI personal assistant arrived with Google Assistant, Siri and Cortana, my framing focussed on trying to communicate that AI was no longer an abstract concept, but part of our everyday lives; albeit in a relatively limited manner. But it was only with the arrival of Amazon Alexa that many people were spending real money to own what is ultimately an AI product. Well… today things feel different again.