Although 11.5 million is a large number, most readers probably had no idea what went into drawing meaningful conclusions from that huge cache of documents. In fact, it took some 400 journalists at more than 100 news organizations an entire year to peruse the 2.6 terabytes of data in those documents and piece together the story of a company that helped the world's wealthiest people set up offshore bank accounts. In a lecture hosted by the University of Delaware Cybersecurity Initiative on Wednesday, April 6, computer scientist James Nolan used the Panama Papers as an example of the need for new machine learning techniques to address the problems associated with living in a data-rich, information-poor world. "Why can't we put that 2.6 terabytes through an algorithm and spit out relationships in a few hours?" he asked. Nolan emphasized the distinction between raw data which is collected from cameras, phones, sensors, satellites, written documents, cyber-logs, and other sources and information, which is the knowledge gained from studying data and teasing out relationships, resolving ambiguities, understanding scenes, and labeling events.

California Rep. Duncan Hunter is reportedly being questioned by the Federal Election Commission over his use of campaign funds to buy video games. The San Diego Union-Tribune reported Hunter listed 1,302 worth of Steam Games on his campaign financial disclosure for the end of 2015, with a note saying "personal expense – to be paid back." The Republican lawmaker has said that the purchases were a mistake by his teenage son, who also made several other unauthorized purchases. The Union-Tribune reported that the purchases run from Oct. 13 to Dec. 16, and no payback was listed during that time period. Joe Kasper, a spokesman for Hunter, said the congressman's son used his father's credit card for one game and then several more charges were made after Hunter tried to close access to Steam.

Read Eduardo Bonet's answer to How are big data, machine learning, and data science affecting the field of education? Your email address will not be published. You may use these HTML tags and attributes: a href "" title "" abbr title "" acronym title "" b blockquote cite "" cite code del datetime "" em i q cite "" strike strong

Too much data and too few people: Firstly, this is a no surprise that machine learning algorithms will work at the pace not matching their counter scientist friends. If trained properly, machine could easily pacify majority of data preparation and analysis demand in data analytics world. Another cool thing about machine learning is that once code is prepped and machine is programmed, you could use it multiple times and multiple places and see the magic happen. The trick is to not overkill first but to use it for overhead tasks first and keep making it more and more sophisticated, so that it will start doing all the heavy lifting and pacifying the resource demand as a result. Hence, machine learning single handedly can reduce big-data resource crunch and make the resource distribution relevant and appropriately.

A convoy of nearly a dozen self-driving trucks has arrived safely in Rotterdam following a cross-border European test run, in one of the first major steps towards future automated trucking. The self-driving truck convoy was part of one of the largest convoys of these semi-automated trucks being tested by a consortium of some of the largest European truck producers, including DAF, Daimler, Iveco, MAN, Scania and Volvo. According to The Guardian, the truck convoy arrived in what are being called'truck platoons', which consist of groupings of between two and three trucks. Within the truck platoon, the three individual vehicles were connected via a wireless signal, with one truck leading and the others following suit in terms of the route the lead is taking, as well as speed. President of the group representing the manufacturers, Eric Jonnaert, said that the concept of truck platoons for self-driving trucks driving at the same speed would have a considerable benefit in terms of reducing traffic on motorways.

While companies such as Google chase the fully autonomous car, Toyota is taking a more measured approach toward a "guardian angel" car that would seize control only when an accident is imminent. But as starkly different as those approaches are, they both will require a wide range of data-intensive technologies, according to Gill Pratt (pictured), chief executive officer of the Toyota Research Institute, a research center focused on AI and robotics. He spoke at the GPU Technology Conference in San Jose today. Toyota has made a huge bet–a billion dollars over five years, in fact–not only on semiautonomous cars but robots that could help older people with indoor mobility. The Toyota Research Institute, which will have facilities near Stanford University and the Massachusetts Institute of Technology, is intended to focus both on what Toyota calls outdoor mobility (cars) as well as indoor mobility (robots).

Make room, stethoscope and otoscope. Artificial intelligence (AI) applications are increasingly among the physician's standard instruments,experts at the University of Toronto say. "With electronic records, you can use text algorithms to read a patient's history, review their genetic predispositions, and correlate the information to make predictions," says Dr. Frank Rudzicz. Rudicz is one of five experts exploring the issues of privacy, accuracy and accountability at The Robot Will See You Now – the Revolution in Artificial Intelligence and Medicine at U of T on April 5. A research scientist with the Toronto Rehab Institute and an assistant professor (status only) in the department of computer science at the University of Toronto, Rudzicz is also a project lead within a federally funded national research network in technology and aging known as AGE-WELL NCE.

Workers looking for jobs in 2035 might consider retraining as remote-controlled vehicle operators or online chaperones. Those are two of the jobs of the future suggested in a report by the CSIRO that charts 20-year trends in increasingly digitally focused and automated Australian workplaces. Related: Automation may mean a post-work society but we shouldn't be afraid The employment minister, Michaelia Cash, released the report on Friday at the Australian Computer Society's conference. Cash said the report showed "some jobs will inevitably become automated over the coming years but technological change will improve others and also create new jobs and opportunities". "The future won't be about people competing with machines, it will be about people using machines and doing work that is more interesting and fulfilling," she said.

Google self-driving car finally causes an accident - a lesson in AI. According to The Verge, Google had recently performed a software update that changed the behavior to be more human like. "So several weeks ago we began giving the self-driving car the capabilities it needs to do what human drivers do: hug the rightmost side of the lane." The truth is that one of the complaints about self-driving cars is that they are too cautious so Google adapted the software so the car would move to the far right of the lane so two cars could fit in the single wide lane. This is what a regular, old fashioned, human being does so cars can move more fluidly though the heavily congested streets of California.

Are bots the new apps? Microsoft chief executive Satya Nadella reckons they are. Bots sometimes get a bad rap, but here are a few that will brighten your feeds. This week, Kik – a messaging app popular with teenagers – launched a "Bot Shop" where users can interact with brands or play games with chat bots instead of talking to their real friends. American Tex-Mex chain Taco Bell launched the TacoBot, which lets you order lunch directly from Slack, a work chat platform.