Even before the blockbuster success of Instagram, there was never a shortage of photo-filtering apps for iOS. To this day, the app store is chock-full of them. But every once in a while, a photo-effect app comes along that generates buzz. Using artificial intelligence technology, the app goes beyond merely filtering by letting your photos mimic the work of modernist masters like Van Gogh and Picasso. Starting Up The free app, for all its wizardry, is just a tiny 15MB download; that's because it performs its magic in the cloud (which can have its own downside, however, as I'll explain later).

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Where we're going we don't need roads, just a large database of pictures. A team at New York University have taught a machine learning system to drive off-road by showing it photos of different landscapes. It's one thing to train driverless cars to navigate city streets or highways. But taking robot drivers off-road is tricky because the surroundings are highly variable, says Karl Iagnemma at the Massachusetts Institute of Technology, who wasn't involved in the work. It is hard to give a robot an exhaustive set of driving rules for every environment.

H2O is the leading open source big data machine learning platform. This talk will cover the distributed parallel in-memory data storage and compute architecture. We will then move on to examples of using H2O from R, Python, Java and Scala. Depending on interest we can also cover Deep Learning in H2O, integration of H2O into smart applications, and/or the optional integration with Spark.

July 6, 2016 – Romonet today announced it is filing for a number of new patents for the next phase of its data center intelligence platform, utilizing the applications of Machine Learning. The company is known as the leader in data center analytics and this development enhances the value of Romonet's already patented solution. Like Google, Amazon, Cisco and Netflix, who already use Machine Learning to personalize services and business intelligence, Romonet's industry-leading platform is revolutionizing the booming global data center market. With Romonet, Hyperscale and Multi-Tenant Data Center (MTDC) operators are improving the services they provide to their customers while strengthening financial management through investment, cost and margin analysis.

Ben Dickson is a software engineer and freelance writer. He writes regularly on business, technology and politics. The transportation industry is associated with high maintenance costs, disasters, accidents, injuries and loss of life. Hundreds of thousands of people across the world are losing their lives to car accidents and road disasters every year. According to the National Safety Council, 38,300 people were killed and 4.4 million injured on U.S. roads alone in 2015.

Some water utilities have so much data at their disposal it is hard to sift through it all and use it effectively, but software has the potential to change that. "One tool for working with potentially valuable truck loads [of data] is an artificial neural network -- a software system that uses machine learning techniques to process tons of data and intelligently answer questions," Ars Technica reported. OmniEarth, a geographic analytics company, is using IBM's Watson technology to give meaning to water data. Watson, a machine learning system, became a household name when it managed to outdo some formidable Jeopardy contestants. The project has deployed this technology to help water managers understand whether ratepayers are using water efficiently.

Artificial Intelligence is the latest hotness. We've heard how bots are going to be the new apps allowing natural conversational interfaces. Siri, Cortana and Google Now are no longer a gimmick and are becoming more useful every day. Machine Learning sits behind artificial intelligence and on the surface it may seem like a deeply technical, scientific topic. We are here to tell you that it is more accessible than you think.

As a UK-focused venture capital investor, Oxford Capital is fortunate that the UK is a world leader in AI (although to avoid topical accusations of British exceptionalism, it's definitely worth mentioning that there are centres of excellence in AI and machine learning (ML) throughout Europe). We have just completed an as-yet undisclosed investment in the AI space, and we're evaluating several other opportunities. Along with taking an interest in AI companies that approach us for funding, we've mapped out recent activity in the sector across the UK. Innovation starts with talented individuals, and AI is no exception. Many of the UK's most respected universities have AI research groups, such as the Intelligent Systems group within UCL and the joint Oxford-Cambridge Strategic AI Research Centre.

The perception of what artificial intelligence was capable of began to change when chess grand master and world champion Garry Kasparov lost to Deep Blue, IBM's chess-playing program, in 1997. Significantly more complex, requiring even more strategic thinking, and featuring an intricate interweaving of tactical and strategical components, it posed an even greater challenge to artificial intelligence. With a number of possible moves per turn an order of magnitude greater than chess, any algorithm trying to evaluate all possible future moves was expected to fail. Led by Hiroaki Kitano and Manuela Veloso, the ambitious goal set that year was to have by 2050 a team of humanoid robots able to play a game of football against the world champion team according to FIFA rules, and win.