As a proof of concept, the researchers set up a publicly available web site called Regex Generator at http://regex.inginf.units.it/ You do so by entering a piece of text and then highlighting the segments to be extracted. After the minimum requirements in the length of text and the number of matches to extract (requires a minimum of 25 highlighted items) are satisfied,the'Evolve!' button becomes enabled. By pressing it you start a run and let the engine come up with the regular expression suitable for the task.

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Engineers are testing a new robot rescue system in the Greek islands, hoping it will be able to save some refugees while trying to cross from Turkey to Greece.

Here's yet another new application of machine learning: MIT has developed a system for fixing errors in bug-riddled code. The new machine-learning system developed by researchers at MIT can fix roughly 10 times as many errors as its predecessors could, the researchers say. They presented a paper describing the new system, dubbed "Prophet," at the Principles of Programming Languages symposium last month. Essentially, the system works by studying patches already made to open-source computer programs in the past in order to learn their general properties. Prophet was given 777 errors and fixes in eight common open-source applications stored in the online repository GitHub.

What are the most interesting things Facebook is doing in ML research? The Applied ML team I am a part of is Facebook's applied research arm. We work on core ML, on computer vision, on computational photography and on language technologies. We work very closely with Facebook AI Research (FAIR) who is pushing the state-of-the-art on these areas, and we are complementary in that we focus more heavily on applications. I would like to highlight a couple of recent pieces of research I find very exciting.

In 2014, Google went on a robot spending spree, buying a handful of companies working on various technologies to help robots see, walk, and grasp objects. It seemed that the company was intent on building advanced new robots that might transform factories and even our homes. But last week Bloomberg reported that Google wants to sell the most striking of the companies it acquired, Boston Dynamics. The company's impressive two- and four-legged robots were apparently too far from being marketable. Google has not given up on robots, but appears to have decided to be more realistic about what it can achieve. "When you're making a product, you have to pick what it's going to do and a price point, and the target customer," says Helen Greiner, who cofounded iRobot, a successful manufacturer of household robots such as the Roomba, and is now CEO of drone builder CyPhyWorks.

The ubiquity of using technology for technology's sake to resolve problems that don't even exist is well documented and the cause of lots of frustration among both consumers and businesses. Thankfully this naive behavior is being replaced with a new refreshing outlook that concentrates on how high-tech computing or automation can deliver real value or make a difference to our lives. Rather than jumping headfirst into solution mode, it increasingly feels that our digital maturity has helped us realize that we need to understand a particular problem fully before even thinking about moving forward in implementing a fix. Recently we had seen clear evidence of this when health workers approached technical experts for help from Google's London-based company DeepMind. The significant challenge faced by hospitals was detecting and communicating problems with patients quickly and efficiently.

From self-driving vehicles and semi-autonomous robots to intelligent algorithms and predictive analytic tools, machines are increasingly capable of performing a wide range of jobs that have long been human domains. A 2013 study by researchers at Oxford University posited that as many as 47% of all jobs in the United States are at risk of "computerization." And many respondents in a recent Pew Research Center canvassing of technology experts predicted that advances in robotics and computing applications will result in a net displacement of jobs over the coming decades – with potentially profound implications for both workers and society as a whole. The ultimate extent to which robots and algorithms intrude on the human workforce will depend on a host of factors, but many Americans expect that this shift will become reality over the next half-century. In a national survey by Pew Research Center conducted June 10-July 12, 2015, among 2,001 adults, fully 65% of Americans expect that within 50 years robots and computers will "definitely" or "probably" do much of the work currently done by humans.