America's tax enforcement agency, the Inland Revenue Service, is pretty sure Paulo Marques is an international tax evader. For the last five years, without fail, he's been summoned by the authorities to spend hours explaining the ins and outs of his revenue streams. But the Inland Revenue's computer doesn't know that, Marques tells the audience WIRED Money 2016. In fact, when it comes to stopping fraud, machines get it wrong far too often. "If you want to stop fraud, you really need to understand human behaviour," says Marques, who founded Feedzai, a company that uses big data to combat fraud.

When we see two people meet, we can often predict what happens next: a handshake, a hug, or maybe even a kiss. Our ability to anticipate actions is thanks to intuitions born out of a lifetime of experiences. Machines, on the other hand, have trouble making use of complex knowledge like that. Computer systems that predict actions would open up new possibilities ranging from robots that can better navigate human environments, to emergency response systems that predict falls, to Google Glass-style headsets that feed you suggestions for what to do in different situations. This week researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have made an important new breakthrough in predictive vision, developing an algorithm that can anticipate interactions more accurately than ever before.

The threat of terrorism has greatly accelerated the exchange of data between European states. Social media has become indispensable, both for investigative purposes and to fight propaganda. The "Fraternity Taskforce", a group of some 20 investigators, has probing into the Paris attacks of 13 November 2015 since late last year. But this team, based at Europol headquarters in The Hague, has no high-tech surveillance equipment or bullet-proof vests. Its main weapon and its biggest resource is data, vast quantities of data. The European police organisation's focus on terrorism has quickly taken off with this investigation.

Above the Trend Line: machine learning industry rumor central, is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. Our intent is to provide our readers a one-stop source of late-breaking news to help keep you abreast of this fast-paced ecosystem. We're working hard on your behalf with our extensive vendor network to give you all the latest happenings. Be sure to Tweet Above the Trend Line articles using the hashtag: #abovethetrendline.

When we see two people meet, we can often predict what happens next: a handshake, a hug, or maybe even a kiss. Our ability to anticipate actions is thanks to intuitions born out of a lifetime of experiences. Machines, on the other hand, have trouble making use of complex knowledge like that. Computer systems that predict actions would open up new possibilities ranging from robots that can better navigate human environments, to emergency response systems that predict falls, to Google Glass-style headsets that feed you suggestions for what to do in different situations. This week researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have made an important new breakthrough in predictive vision, developing an algorithm that can anticipate interactions more accurately than ever before.

On 14 June, news broke that someone had hacked into computers at the US Democratic National Committee, exposing opposition research on Republican presidential candidate Donald Trump, as well as a trove of chat logs and emails. Some blamed Russia – although as ever details are unclear. The same day, NATO announced that it was designating cyberspace as an "operational domain" for war alongside land, sea and air. Reports of one country attacking the computer systems of another – like this week's hack on the Democrats, last year's Chinese breach of the US Office of Personnel Management, or North Korea's attack on Sony in 2014 – have become common. The details of hacks may differ, but the story is a familiar one. Does NATO's announcement change anything?

Big data platform vendors are increasingly focusing on churning through unstructured data, especially for text, audio and even security applications like insider threat analysis. Among the companies emerging in this industry segment is Digital Reasoning, a well-connected cognitive computing company that has helped the U.S. military track terrorists online while working with financial markets to spot insider trading. The company, which recently expanded beyond the Capital Beltway to Nashville, rolled out the latest version of its Synthesys cognitive computing platform this week that combines machine learning, natural language processing, computer vision and pattern recognition. The combination is intended to boost the quality of unstructured data analysis while reducing the amount of time needed to get the desired results. Version 4 of the Digital Reasoning platform released on Tuesday (June 21) is based on proprietary analytics tools that apply deep learning neural network techniques across text, audio and images.

Federal regulators just opened the skies to commercial drones, with guidelines that include more than a few caveats designed to encourage entrepreneurs while protecting everyone else. The FAA, which announced the rules today, hopes to facilitate innovative uses for the technology like bringing the Internet to remote areas while avoiding the idiocy of drones interfering with firefighting operations or delivering contraband to prisons. "We are taking a careful and deliberate approach that balances the need to deploy this new technology with the FAA's mission to protect public safety," says FAA chief Michael Huerta. The rules let anyone 16 or older who wants to make a business of flying a drone simply do so. In the past, pilots who hoped to make a buck with drones by, say, inspecting power lines, needed FAA permission, a process that could take months.

Artificial intelligence has gained serious traction within the technology community as a solution for complex problems, though in January 2015, Bill Gates observed robotics and artificial intelligence are entering a period of rapid advances. For example, Google, Apple, and Microsoft are competing to transform vehicle transport with self-driving vehicles. In manufacturing, autonomous production enables companies to adapt products to diverse consumer markets and many more. Unmanned drones provide sustained surveillance and swift attacks on targets, and small robots are used to disarm improvised explosive devices. The military is currently funding research to produce more autonomous and self-aware robots to diminish the need for human soldiers to risk their lives.

Since I noted Timothy Tuttle of Mindmeld's LSA16 comments about the sudden increase in the volume of voice search queries, I've noticed an increasing number of articles on the subject. If the attention being given voice search is an indication of its anticipated impact on the marketplace, then it's going to be a big deal. The potential for voice search to become a major search medium is well illustrated by the number of slides Mary Meeker devotes to the topic in her annual Internet Trends report that was just released this month. Out of 213 slides, Mary included 23 slides on voice search. And while the numbers on voice search growth vary quite widely, they all agree on one trend: explosive growth.