The U.S. Air Force has awarded BAE Systems' U.S. subsidiary a three-year, 9.4 million contract to help the service branch develop, integrate and demonstrate a machine learning platform. BAE Systems Inc. will explore latest machine learning advancements to support the Air Force's efforts to apply analytics to address space situational awareness challenges as well as leverage high-performance computing and reasoning visualization architectures, the Defense Department said Friday. The Air Force also seeks to increase its ability to detect and predict new complex scenarios through the project. BAE systems will perform the services in Massachusetts and Virginia and is scheduled to finish July 15, 2019. The Air Force Research Laboratory obligated 868,750 in fiscal 2016 research, development, test and evaluation funds at the time of award.

Coding will join this list in time, however, where it differs wildly from the afore mentioned examples is it is unlikely to be lovingly preserved for future generations to admire, fiddle with or better still, reactivate. Its essence will not be reified for one specific reason – it can't be touched and humans value tactility. We touch immediately, both inside and outside the womb. Today, we find ourselves at a pivotal moment in our existence and about to experience an exponential period of rapid technological growth the likes of which is quite probably beyond our comprehension and at a base level, will have serious implications for coding. We rather arrogantly think that because we have a good grasp of our own technological advancement so far, we can somehow predict the mass cultural and behavioural shift about to happen as we question our own skills in the world. Us techies hold on to the notion that we are the masters of code, and we will be forever commanding line by line, the computers to do our bidding.

Using the power of analogy, a new structure-mapping engine gives computers the ability to reason like humans and even solve moral dilemmas. Northwestern University's Ken Forbus is closing the gap between humans and machines. Using cognitive science theories, Forbus and his collaborators have developed a model that could give computers the ability to reason more like humans and even make moral decisions. Called the structure-mapping engine (SME), the new model is capable of analogical problem solving, including capturing the way humans spontaneously use analogies between situations to solve moral dilemmas. "In terms of thinking like humans, analogies are where it's at," said Forbus, Walter P. Murphy Professor of Electrical Engineering and Computer Science in Northwestern's McCormick School of Engineering.

Peering deeper and deeper into space will require telescopes with huge mirrors, but building, testing, and transporting those super-scopes will be a daunting challenge, a conference of future space leaders was told Thursday. Alberto Conti, a Northrop Grumman manager, said the James Webb Space Telescope, currently undergoing tests, has a mirror that's about 21 feet in diameter. Even at that size, Conti said it is difficult to find a facility large enough to test the mirror and a spacecraft that can transport it to the orbiting International Space Station. His solution, echoed by Jay Falker of NASA, is to use robots to begin building and testing the telescopes – in space, where there's plenty of elbow room. Robots in space were just one of the "wicked cool technologies" introduced at the Future Space Leaders conference on Capitol Hill last week.

DARPA are starting a competition to help automate defence and see how artificial intelligence can combat cyber-threats. The latest DARPA Grand Challenge is looking to artificial intelligence to seek out and destroy vulnerabilities in software. The US Defense Advanced Research Projects Agency (DARPA) Cyber Grand Challenge will see seven teams battle it out to see if machine learning can do better in finding and fixing exploits better than humans. The agency said on its competition website that identifying threats and remediating them can take over a year from first detection to the deployment of a solution, by which time critical systems may have already been breached. "This slow reaction cycle has created a permanent offensive advantage," reads the blurb.

Machine learning is set to go mainstream in the next two years, according to a new survey by software and application development vendor SoftServe Inc. The new report, based on an April poll of 300 U.S. and U.K.-based medium and large enterprises, shows that 62 percent of firms expect to roll out machine learning-based tolls for business analytics within the next two years. The majority of those companies said the most promising opportunity for machine learning lays in real-time data analysis. According to SoftServe, the survey is evidence that machine learning is moving past the "hype cycle", with enterprises looking to automate analytics processes in areas like business intelligence and cyber security. In the latter area, further evidence of machine learning's progress comes from the Defense Advanced Research Projects Agency (DARPA), which is sponsoring an "all-machine" hackathon at the DEF CON hacking conference in Las Vegas next month.

They were the mischievous creatures blamed for causing mechanical failures and faults on aircraft during World War Two and later the destructive monsters in a hit film franchise. So Gremlins might not seem like the first choice for a fleet of robotic aircraft being developed by the US military. But the US Defense Advanced Research Projects Agency is developing swarms of re-usable drone aircraft that can work together to perform a mission, which it has called the Gremlins program. Darpa said the program has been deliberately named Gremlins after the imps that British pilots during Wold War Two adopted as their good luck charms. The idea is to replace the expensive and increasingly vulnerable multi-function combat aircraft which currently perform a range of different missions.

Robot" débuted, last year, it felt like a shock to multiple systems, one of them being the network on which it aired. That was USA, a subsidiary of NBCUniversal and Comcast; the home of upbeat, aspirational procedurals, it's known as the "blue skies" network. Robot" was more of a hurricane advisory. Created by a newcomer, Sam Esmail, it was a parable of class rage, with a vigilante anti-hero, welding the paranoid style in American TV drama onto the ideology--and, just as important, the aesthetics--of both the Occupy movement and Anonymous. Esmail's plot was a Philip K. Dick puzzle box, exposing one false reality after another.

A major concern for our rights as consumers is the way that machines direct us according to their interests and not ours. Experts such as Dr Jonathan Cave warn about the growing influence of software machines on our lives. Cave says that software machines will make use of what they know about us to present information to us which may not be to our advantage. Because the search engines that we have used know a certain amount about us and our previous buying decisions, they are keen to exploit that by turning us into a buyer of something, by a process known as'filter bubbles' – a feedback loop where recommendations only reinforce existing patterns. As Dr Rupp states'if you are not paying then you are not the customer'. Thus if you are not paying for an internet technology such as Google or Facebook it is not acting in your interests, but rather in the interests of the customers who are paying to present information to you.

Tesla Motors is trying to see if it can make improvements in its Autopilot partial self-driving system, which may have been a factor in a recent fatal accident. He said "significant improvements" look possible that would be beamed to Tesla's electric cars wireless via over-the-air updates. The National Highway Traffic Safety Administration opened an investigation. Last week, the National Transportation Safety Board sent its own team to look into the safety of the system.