Blizzard made a very curious announcement about Starcraft II at BlizzCon 2016. Instead of a new expansion pack, the game is instead being opened up to Google's Deepmind project; and will teach the AI system how to play an RTS. Deepmind made headlines earlier this year when its AlphaGo AI managed to beat a world class Go player; a feat that was believed to be impossible. The number of possible actions in Go was originally thought to be too great for a computer to calculate within the time constraints of a professional match. Despite this, Deepmind pulled off a 4 – 1 victory over Lee Sedol.

Data science is fast becoming a critical skill for developers and managers across industries, and it looks like a lot of fun as well. But it's pretty complicated - there are a lot of engineering and analytical options to navigate, and it's hard to know if you're doing it right or where the bear traps lie. In this series we explore ways in to making sense of data science - understanding where it's needed and where it's not, and how to make it an asset for you, from people who've been there and done it. This InfoQ article is part of the series "Getting A Handle On Data Science" . You can subscribe to receive notifications via RSS. Enterprises are increasingly realising that many of their most pressing business problems could be tackled with the application of a little data science.

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) has signed on for a pair of Nvidia DGX-1 3U boxes to serve as a platform for applying machine learning to its science. Angus Macoustra, acting deputy CIO and executive manager for Scientific Computing at CSIRO, said the boxes would be used for medical image analysis, nano-material modelling, genome analysis, astronomy, and space science. In the realm of space science, Macoustra said machine learning can help with hunting for the signature of pulsars. "Two thirds of all known pulsars discovered in the world have actually been observed on the Parkes radio telescope, and CSIRO holds close to 40 years of data collected from that instrument," Macoustra said during the GTCx Australia conference on Tuesday. "Machine learning gives us mechanisms to interrogate that data and it is the belief of our scientists that there are still a number of unknown pulsars locked up in these data sets that span the past 40 years."

Have you ever been in a situation where knowing another language would have come in handy? I remember standing on the platform at Tokyo Station watching my train to Nagano -- the last train of the day -- pulling away without me on it. What ensued was a frustrating hour of gestures, confused smiles, and head-shaking as I wandered the station looking for someone who spoke English (my Japanese is unfortunately nonexistent). It would have been really helpful to have a bilingual pal along with me to translate. Bilingual pals can be hard to find, but Google's new translation software may be an equally useful alternative.

Dynamic programming is a technique that can yield relatively efficient solutions to computational problems in economics, genomic analysis, and other fields. But adapting it to computer chips with multiple "cores," or processing units, requires a level of programming expertise that few economists and biologists have. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Stony Brook University aim to change that, with a new system that allows users to describe what they want their programs to do in very general terms. It then automatically produces versions of those programs that are optimized to run on multicore chips. It also guarantees that the new versions will yield exactly the same results that the single-core versions would, albeit much faster.

Artificial intelligence has a problem with nuance but that didn't stop it from correctly predicting the outcome of most of the cases An artificial intelligence system has correctly predicted the outcomes of hundreds of cases heard at the European Court of Human Rights, researchers have claimed and, what makes the announcement perhaps even more staggering is that it was right 79% of the time. While AI is increasingly being used in fields such as journalism, law and accountancy critics so far have said no AI would be able to understand the nuances of a legal case, but now, ironically, it might look as if their own case is being undermined. The study, which was conducted by researchers at University College London and the universities of Sheffield and Pennsylvania does not spell an end to lawyers – yet – but it does potentially set AI on the road to becoming judge, jury and, well, you know. "There is a lot of hype about AI but we don't see it replacing judges or lawyers any time soon. What we do think is they'd find it useful for rapidly identifying patterns in cases that lead to certain outcomes," said Dr Nikolaos Aletras, who led the study at UCL. "It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights."

Researchers from Princeton University received mass media attention when they recently predicted the demise of Facebook. Data scientists at Facebook soon hit back with their own'study:' "In keeping with the scientific principle (used by Princeton) 'correlation equals causation,' our research unequivocally demonstrated that Princeton may be in danger of disappearing entirely." Is it surprising that the original Princeton study found its way onto the front pages of newspapers and magazines across the world? Probably not – the fact is statistical results with a causal interpretation have a stronger effect on our thinking than non-causal information. What the data scientists at Princeton relied upon in presenting their paper was our individual human inability to think statistically.

Waiopehu College pupils, from left, Kate Nicholson, Niko Tofa and Sammy Heyward. More than 100 teens have explored the ever-evolving world of artificial intelligence. The 130 budding young scientists, from Freyberg High School, Manawatu College and Waiopehu College, learned about the benefits and difficulties faced in a technology-rich future at a conference in Levin on Friday. Mechanical masseuses and construction robots that could work in all weather conditions and give workers a sleep-in were among ideas the pupils – aged 11 to 13 – came up with for the future. Centre for Science and Citizenship founders Dr Deborah Stevens, left, and Dr Lynne Bowyer.

This piece showcased the immense power of exponential technology versus linear technology and became a pivotal concept for anyone trying to anticipate what the future held. The essay predicted advances in business and technology with eerie precision, including how exponential growth would ripple through any technology that became an information technology, such as computing, biotechnology, or energy. The past 15 years have shown that while some of Kurzweil's specific predictions may or may not pan out exactly as predicted, the underlying idea of the law of accelerating returns grows more relevant with each passing week. But as we start to look at the next fifteen years, I believe there is another concept just as significant as the law of accelerating returns that we need to understand. The strangest, most interesting and magical-seeming creations of the future will occur at the intersection of multiple exponential trend lines.

Vyacheslav is a PhD candidate at the Oxford Internet Institute. His research uses social psychology and machine learning to understand networks of people and networks of ideas. Imagine a typical day in 2020: Your personal AI assistant wakes you up with a friendly greeting before preparing your favorite breakfast. During your morning workout, it plays new songs that perfectly match your musical tastes. For your driverless commute to work, it has pre-selected a few articles based on the duration of your commute and what you've read in the past.