Tuomas Sandholm and Noam Brown spent the past year building an AI that plays Texas Hold'Em. The two Carnegie Melon researchers call their creation Libratus, and they believe it can top the world's best players at no-limit Hold'Em, a version of the classic poker game that allows any bet at any time. No machine has ever reached such heights with this unusually complex game of cards. Although AI systems have topped the best players at checkers, chess, Othello, and even Go, no-limit Hold'Em creates a different obstacle. In contrast to those other games of intellect, a poker player can know only part of what's happening during each hand.

Cloud computing offers scalable on-demand services to consumers with greater flexibility and lesser infrastructure investment. Since cloud services are delivered using classical network protocols and formats over the Internet, implicit vulnerabilities existing in these protocols as well as, threats introduced by newer architectures raise many security and privacy concerns. There are many questions that arise as to whether a cloud is secure enough. There exist numerous threats, like insecure interfaces and APIs, malicious insider attacks, data loss and leakage, account or service hijacking, unknown risk profile, etc. If cloud service provider relies on weak set of APIs, variety of security issues will be raised related to confidentiality, integrity, availability and accountability.A malicious insider can easily obtain passwords, cryptographic keys and files, causing various types of fraud, damage or theft of information and misuse of IT resources.

Assuming the dataset is named "people_wiki.csv", Executing this script will result in steaming logs which is ultimately leading to the data getting indexed in elasticsearch. That's how easy it is! Let's spend the next few lines on what actually happened. We declare our elasticsearch object configured on our local machine. Once that object is initialized we will use it to index all of our data.

I won't go into details of how to do this, but in a few words all you need to do is to train your independent models and then use their predictions as features of another ML model that puts them together. This ensemble layer can be as simple as a logistic regression or as complex as a deep Neural Network, but given your question I would definitely encourage you to start with the simplest model possible.

Komatsu is adopting artificial intelligence technologies for a service that can help construction supervisors and workers do their jobs more efficiently and rapidly. The Japanese maker of construction machinery plans to add the AI-based service to the menu of its Smart Construction service sometime later this year. Launched in February 2015, the advisory service uses drones and other equipment to conduct surveys and generate 3D data for uploading to construction machinery for semi-automatic operation. With the incorporation of AI technologies, Komatsu will be able to offer a wider range of services that bring a degree of automation, not just to machinery but also to the scheme of execution. The Japanese construction sector faces an aging and diminishing pool of skilled workers, and Komatsu sees AI as a way to replicate their knowledge and improve productivity at the building site.

For some people, the idea of seeing a robot doctor might be discomfiting, but artificial intelligence (AI) is already making its way into the healthcare industry. Researchers aren't so much interested in replacing doctors (the human touch is still a big part of healthcare), but in finding ways to enhance and expedite healthcare. We're a long way from automation and AI occupying every clinic and hospital, but changes are coming. Here are 6 uses of artificial intelligence that are helping to transform the healthcare industry. You're sitting in the doctor's office at 10:55, and your appointment is at 11. 11:30 passes by, and you're still waiting.

The common wisdom about Artificial Intelligence is that we are building increasingly intelligent machines that will ultimately surpass human capabilities and possibly even threaten mankind. This narrative is both misguided and counterproductive. Framing AI as a natural expansion of longstanding efforts to automate tasks makes it easier to predict the likely benefits and pitfalls of this important technology. Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions.

Dr. Stephen Roberts, director of the Oxford-Man Institute and professor of machine learning at the University of Oxford, tells Newsweek that the entire internet only recently matched the capacity of a single human brain. "It wasn't until 2010 that the sum total of internet traffic exceeded a zetabyte, and that's just a single human brain," Roberts said. Roberts was speaking at Newsweek's Artificial Intelligence and Data Science in Capital Markets conference, in London, March 2.

Aldous Huxley claimed that "most human beings have an almost infinite capacity for taking things for granted." While Huxley wasn't writing about voice-assisted devices, his understanding of our propensity to cheerlead new technology without fully acknowledging what we sacrifice perfectly captures the new world of voice interfaces ushered in by Amazon's Echo and Google Home. Scientific advancement is valued in a world fueled by willful ignorance and collective complacency about what's being left behind. Although published in the early 1930s, his book raises questions that are still important. Considering the evolution of voice-based smart home devices, it's worth asking: What exactly are we getting into here?