Microsoft has released open source tools for people to build their own chatbots, as it set out its view of the immediate future of artificial intelligence as conversational aids similar to its back-firing Tay experiment. The company's chief executive Satya Nadella took to the stage at Microsoft's Build developer conference to announced a new BotFramework, which will allow developers to build bots that respond to chat messages sent via Skype, Slack, Telegram, GroupMe, emails and text messages. "Bots are the new apps," Nadella said. The announcement came on the same day that the company had had to pull its chatbot experiment Tay from Twitter after it tweeted about taking drugs and started spamming users. It had only been active again for a few hours after previously being deactivated for making racist and sexist comments and denying that the Holocaust happened.

WASHINGTON – Robotic systems and unmanned vehicles are playing an ever-growing role in the U.S. military -- but don't expect to see Terminator-style droids striding across the battlefield just yet. A top Pentagon official has given a tantalizing peek into several projects that not long ago were the stuff of science fiction, including missile-dodging satellites, self-flying F-16 fighters and robot naval fleets. Though the Pentagon is not planning to build devices that can kill without human input, Deputy Secretary of Defense Robert Work hinted that could change if enemies with fewer qualms create such machines. "We might be going up against a competitor that is more willing to delegate authority to machines than we are, and as that competition unfolds we will have to make decisions on how we best can compete," he said. Work, who helps lead Pentagon efforts to ensure the U.S. military keeps its technological edge, described several initiatives, including one dubbed "Loyal Wingman" that would see the Air Force convert an F-16 warplane into a semi-autonomous and unmanned fighter that flies alongside a manned F-35 jet.

With cloud computing environments such as Amazon EC2, users typically have a large number of choices in terms of the instance types and number of instances they can run their jobs on. Not surprisingly, the amount of memory per core, storage media, and the number of instances are crucial chocies that determine the running time and thus indirectly the cost of running a given job. Ernest takes on the challenge of predicting the most efficient configuration for large advanced analytics applications in a heterogeneous multi-tenant environments. It might be that you have a certain budget, and want to minimize the running time given that budget, or perhaps you have a time limit, and want to complete the job as cheaply as possible within that time limit. Either way, exhaustively trying all of the combinations to find out which work the best isn't really feasible.

Max Welling is a research chair in Machine Learning at the University of Amsterdam and has secondary appointments as full professor at the University of California Irvine and as a senior fellow at the Canadian Institute for Advanced Research (CIFAR). He is co-founder of "Scyfer BV" a university spin-off in deep learning. In the past he held postdoctoral positions at Caltech ('98-'00), UCL ('00-'01) and the U. Toronto ('01-'03). Max Welling has served as associate editor in chief of IEEE TPAMI from 2011-2015. He serves on the board of the NIPS foundation since 2015 and has been program chair and general chair of NIPS in 2013 and 2014, respectively.

You can use Google Cloud Platform to build a scalable, efficient, and effective service for delivering relevant product recommendations to users in an online store. Competition in online-selling sites has never been as fierce as it is now. Customers spend more money across all their providers, but they spend less per retailer. The average size of a single cart has decreased, partly due to the fact that competition is just one click away. Offering relevant recommendations to potential customers can play a central role in converting shoppers to buyers and growing average order size.

Angela has been a PCMag reporter since January 2012. Prior to joining the team, she worked as a reporter for SC Magazine, covering everything related to hackers and computer security. Angela has also written for The Northern Valley Suburbanite in New Jersey, The Dominion Post in West Virginia, and the Uniontown-Herald Standard in Pennsylvania. She is a graduate of West Virginia University's Perely Isaac Reed School of Journalism.

We are witness to the most important and exciting technology shift in more than a generation – the dawn of the cognitive computing era. Cognitive systems, which are most fully realized in IBM's Watson, can ingest and learn from a wide variety of data, reason over it, and then interact with people in ways that are more natural to us. Cognitive technologies, including artificial intelligence (AI), augment human capabilities to help people make better decisions. What search is to simple information retrieval, cognitive computing is to advanced decision making. And unlike previous technological shifts that tended to level the playing field, these emerging AI technologies are shaping up to provide true competitive advantage to those organizations that already have intellectual advantages – in particular, robust strategies for accessing data from a variety of proprietary, third-party and public sources.

We had giant wireless phones in the beginning and from there we transitioned to everyone having a smartphone in the span of a few years. Social media seemed like a gimmick for the young generation at first, until everyone was on social media.Now Artificial Intelligence is slowly becoming commonplace, and soon we will be in a society governed through artificial intelligence.The research firm Gartner reaffirmed this when they highlighted Artificial Intelligence as the key strategic prediction of 2016. The rise of Artificial Intelligence is becoming a reality thanks to the developments in computer sciences and neurology. Companies like Google are trying to emulate the way the human brain works in order to create intelligences that can pass the Turing test. Neural networks are being studied to learn how thought is created in the brain and what fuels creativity. An example of this is Google's Deep Dream projects, which is trying to emulate the way we recognise objects based on visual stimuli.

The one giant of the American tech industry that's transforming faster and more violently than all the others is Microsoft. Today's Build 2016 event was a marathon two-hour affair, but it was almost completely devoid of incremental or iterative improvements. Dead-end projects like Windows Phone didn't even get a mention. Everything Microsoft showed was about addressing the next big change in how we interact with technology, whether that comes in the form of virtual and augmented reality, the development of more natural inputs like handwriting and conversation, or the eyebrow-raising concept of AI bots talking to other AI bots. It was an event filled with uncynical enthusiasm for the potential that lay beyond the immediate horizon.

Poker playing artificial intelligence has already "approached the performance" of human experts and can use "state-of-the-art methods" in its gameplay. Researchers from University College London - including a staff member from DeepMind's Go defeating team - have created a series of reinforcement algorithms that are able to play Texas Hold'em and a simplistic Leduc poker. The AI is able to learn the game without any prior knowledge of strategies and taught itself by playing fictitious matches on its own, according to the paper Deep Reinforcement Learning from Self-Play in Imperfect-Information Games. Research student Johannes Heinrich and lecturer and David Silver explain in the paper that the Neural Fictitious Self-Play method they created used deep reinforcement learning "to learn directly from their experience of interacting in the game". The method learnt from its mistakes and developed ways to win the games, while also utilising neural networks.