Roughly half of all Web traffic comes from bots and crawlers, and that's costing companies a boatload of money. That's one finding from a report released Thursday by DeviceAtlas, which makes software to help companies detect the devices being used by visitors to their websites. Non-human sources accounted for 48 percent of traffic to the sites analyzed for DeviceAtlas's Q1 Mobile Web Intelligence Report, including legitimate search-engine crawlers as well as automated scrapers and bots generated by hackers, click fraudsters and spammers, the company said. DeviceAtlas is owned by Afilias, which calls itself the world's second-largest Internet domain name registry. Bot technologies have long been known to account for a significant amount of traffic, but today they're becoming more malevolent--and more expensive, said Ronan Cremin, CTO of DotMobi, a mobile content delivery company also owned by Afilias.

Google will release the code to it's SyntaxNet language understanding A.I. Language is a big ambiguous soup. Words have different meanings in different contexts, homographs exist, and humans regularly warp the established lexicon with slang. It's almost a miracle that we've built computers that can understand us at all. Systems for understanding human language have advanced significantly in the last few years, as researchers have improved approaches to artificial intelligence like deep learning. These methods set algorithms crawling through immense troves of data to draw connections between words and phrases.

Machine Learning is not a new subject but is becoming an increasingly hotter topic. We have three speakers to each bring a different spin on the subject and therefore it should be a night where there will be something for everyone, whether you are Data Scientist, Analyst or Digital Marketer. Harvinder leads a team of analysts to deliver data-driven customer insight, marketing optimisation and predictive analytics for Moneysupermarket from one of the largest customer databases in the UK with records for 23 million unique individuals. Harvinder was previously Insight Director for Tesco Clubcard at Dunnhumby and Senior Manager for Customer Strategy and Insights at Lloyds Banking Group.He is passionately interested in Data Science, Machine Learning, Big Data technologies and how they can be used to improve Customer Experience. Harvinder will be showing some live models used at MoneySuperMarket.

Bookmark this page by right-clicking here and choosing "Add to Favorites" The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is requesting information on research related to the investigation and characterization of fundamental limits of machine learning with supportive theoretical foundations. Although the main focus is on machine learning, extensions and implications for human-machine systems are also of interest. The notion of fundamental limits here means that the conclusion about achievable performance limits should hold independent of specific learning methods or algorithms.

One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology. "I really feel like I missed the mark in giving the correct amount of feedback," he wrote, pleading to revise an assignment. Thirteen minutes later, the TA responded. "Unfortunately, there is not a way to edit submitted feedback," wrote Jill Watson, one of nine assistants for the 300-plus students. Last week, Mr. Wilson found out he had been seeking guidance from a computer.

The Go challenge is finally over. And it seems that humanity lost; however, we did score one victory, so that's something. Lee Sedol, the 18 time world champion of Go, beat Google's artificial intelligence program this past Sunday, but the AI program snatched the ultimate victory. The Go-playing AI AlphaGo just beat the world-class player for a fourth time, winning the five-game series 4-1 overall. However, the final win was a little tenuous for a time. As Tweets from DeepMind founder, Demis Hassabis, who live Tweeted the event, reveal.

Robots have transformed the lives of tradesmen and laborers, but lawyers, architects, and doctors tend to believe that their careers are safe from the advances of artificial intelligence. This belief is entirely wrong, according to the upcoming book, Future of the Professions: How Technology will Transform the Work of Human Experts. The authors, Richard Susskind, UK government advisor and visiting professor at Oxford Internet Institute, and his son Daniel Susskind, lecturer at Oxford University, have conducted a hundred interviews and drawn on economic and sociological theory to reach their challenging conclusion: AI will dramatically transform the middle-class working landscape. In the near-term, the Susskinds argue, artificial intelligence will simply accelerate the efficiency of professions. But then robots will start to take over more work, and humans will find the roles of "doctor" or "lawyer" replaced with such less glamorous-sounding titles as "empathizer," "knowledge engineer," or "system provider."

The German transport ministry says General Motors' Opel division has been asked to appear before a commission looking into diesel emissions controls after an environmental group claimed two of its models are able to reduce pollution controls. The environmental group, DUH, says it has tested Opel's Zafira and Astra models and claims they reduce pollution controls at some speeds and temperatures. DUH wants them taken off the road. Opel says DUH's tests weren't objective or scientifically grounded, saying "our software was never designed to cheat or deceive." Apparently referring to the computer expert who examined the software for DUH, the company said that "the isolated conclusions of a hacker do not reflect the complex interdependencies of a modern exhaust after-treatment system."

In this talk Blaise Agüera y Arcas, Principal Scientist at Google, will begin by taking a close look at what has been achieved in machine intelligence (especially deep learning) over the past decade, with examples of current techniques and applications from the Machine Intelligence on Devices group at Google and from the community. This includes not only classification and semantic understanding of natural stimuli, but also language, gameplay, and even art. From here Blaise will zoom out and consider some broader questions about human progress, labour and identity in an era of "technological reproducibility". Blaise Agüera y Arcas is Principal Scientist at Google where he leads a team focusing on Machine Intelligence for mobile devices - including both basic research and new products. His group works extensively with deep neural nets for machine perception, distributed learning, and agents, as well as collaborating with academic institutions on connectomics research.

In the past year, we've seen tremendous progress in AI. We've seen AlphaGo defeat a top-level Go professional, a feat even AI experts thought was years away. We've seen computer-assisted self-driving cars. We've seen computers produce imitation Rembrandts by analyzing existing works of art. Bots now participate in conversations and carry out repetitive tasks within enterprise communications platforms.