Trader Navinder Singh Sarao, who is resisting market manipulation charges, at Westminster Magistrates' Court In Robert Harris's 2011 novel The Fear Index a secretive hedge fund builds a computer capable of making its own trading decisions. Gobbling up information, the machine starts to confuse its human creators by building huge stakes and making a handsome profit from a market panic. As they assess the outcome, one of the protagonists notes: "The beauty of it is that it was but 0.4 per cent of total market volatility. No one will ever notice, except us." As markets increasingly rely on computer algorithms, reality is imitating fiction: artificial intelligence is becoming a bigger part of investing and it is also helping regulators ensure that traders do not get away with bad behaviour.

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

The artificial intelligence, dubbed ALPHA, was the victor in that simulated scenario, and according to Lee, is "the most aggressive, responsive, dynamic and credible AI I've seen to date." Details on ALPHA -- a significant breakthrough in the application of what's called genetic-fuzzy systems are published in the most-recent issue of the Journal of Defense Management, as this application is specifically designed for use with Unmanned Combat Aerial Vehicles (UCAVs) in simulated air-combat missions for research purposes. The tools used to create ALPHA as well as the ALPHA project have been developed by Psibernetix, Inc., recently founded by UC College of Engineering and Applied Science 2015 doctoral graduate Nick Ernest, now president and CEO of the firm; as well as David Carroll, programming lead, Psibernetix, Inc.; with supporting technologies and research from Gene Lee; Kelly Cohen, UC aerospace professor; Tim Arnett, UC aerospace doctoral student; and Air Force Research Laboratory sponsors. ALPHA is currently viewed as a research tool for manned and unmanned teaming in a simulation environment. In its earliest iterations, ALPHA consistently outperformed a baseline computer program previously used by the Air Force Research Lab for research.

Financial institutions have a regulatory requirement to monitor account activity for anti-money laundering (AML). Regulators take the monitoring and reporting requirements very seriously as evidenced by a recent set of FinCEN fines. One challenge with AML is that it rarely manifests as the activity of a single person, business, account, or a transaction. Therefore detection requires behavioral pattern analysis of transactions occurring over time and involving a set of (not obviously) related real-world entities. For large transactions, banks file Currency Transaction Reports (CTR) that are used by FinCEN for processing and analysis.

Cognovi Labs is a new analytics startup that relies on Twitris, a Wright State University-developed tool that claims to be able to take a sample of social media chatter about a specific topic and deduce real-time, large-scale, automated sentiment about the specific topic they are researching. As a real-world example of the tool's capability, the Cognovi Labs research team -- led by Wright State University researcher (and Cognovi Labs inventor) Dr. Amit Sheth -- analyzed Twitter chatter leading up to the Great Britain/European Union Membership Referendum (Brexit) on June 23. The team was able to predict some six hours before the news broke that the polls leaning toward the "remain" camp were incorrect. This was predicted by running Twitter chatter through the Cognovi Labs Twitris tool. The machine learning tool leverages Cognovi Labs' semantic intellectual property to be able to automate and extract aggregate meaning from social media chatter (including slang) in new, more precise ways.

Ask Apple's Siri digital assistant if she's evil, and she'll respond curtly, "Not really." Repeat a famous line from the movie "2001: A Space Odyssey," in which a computer on a spaceship kills nearly all the human crew, and Siri groans. And who can blame her? We humans have a morbid fascination with machines rising up to wipe us out or to enslave us as cocooned, flesh-and-blood battery packs. You can see that vision of the future streaming over Netflix whenever you want.

Score one for the combat geeks, after the news broke this week that a computer defeated a human fighter pilot in a virtual dogfight. For years, there has been a debate between those who sees drones as the inevitable future of air combat, and those who insist that a human must always be in the cockpit. But the drone crowd received a boost after researchers devised an artificial intelligence, or AI, that bested a human pilot in aerial combat. Sound too good to be true? The problem with designing a combat AI is that are so many variables to consider in combat, and those variables are so broad that the computer becomes overloaded. So scientists at software firm Psibernetix, the University of Cincinnati and the Air Force Research Laboratory devised ALPHA, an AI that uses "fuzzy logic" to calculate optimum tactics for questions such as which maneuvers to employ and which targets to engage.

United States President Barack Obama's administration said Friday that up to 116 civilians have been killed by U.S. drone strikes in Pakistan, Yemen and other countries where America is not at war. Obama's goal for the release of the numbers is reportedly to create greater transparency about the actions of the U.S. military and CIA in counterterrorism measures against militants plotting attacks against the United States. The announcement covered strikes from the day Obama took office in January 2009 through Dec. 31, 2015. The report by National Intelligence Director James Clapper said the U.S. conducted 473 counterterror strikes, including those by unmanned drones, in this period. Even though the report does not mention the countries where the attacks were carried out, the Associated Press (AP) reported that the Defense Department and CIA have pursued targets in Pakistan, Yemen, Somalia and Libya.

WASHINGTON – The United States on Friday lifted the lid on one of the most controversial tactics of President Barack Obama's secretive counterterrorism campaign, detailing for the first time the number killed in airstrikes in countries like Pakistan and Libya. The White House also released an executive order outlining the steps that should be taken to reduce civilian casualties in America's battle against violent extremism. In a much-anticipated report, National Intelligence Director James Clapper provided fatality estimates for the 473 strikes between 2009 and 2015 that were conducted outside America's principal war zones in Iraq, Syria and Afghanistan. He said between 64 and 116 civilians were killed, and up to 2,581 combatants. Such attacks are typically conducted via drones, though manned warplanes and missiles have also been used.

Roboticists covered a sweeping range of topics at Xconomy's annual Robo Madness West conference last week, from the ethics of artificial intelligence to the powerful impact of robots that have faces. Two themes ran through all the panel discussions, whether they focused on robot design, logistics and manufacturing, drones, or artificial intelligence. Hardware--Ways to make a killing by making cheaper, better versions of certain components. People--In various roles, they make up some of the thorniest challenges to the growth of the robotics/AI sector. Let's talk about hardware first. While robot developers are benefiting from the availability of some cheap, commodity components to build their prototypes, there seems to be plenty of room for innovation, according to the Robo Madness panelists.