Carnegie Mellon's No-Limit Texas Hold'em software made short work of four of the world's best professional poker players in Pittsburgh at the grueling "Brains vs. Artificial Intelligence" poker tournament. Poker now joins chess, Jeopardy, go, and many other games at which programs outplay people. But poker is different from all the others in one big way: players have to guess based on partial, or "imperfect" information. "Chess and Go are games of perfect information," explains Libratus co-creator Noam Brown, a Ph.D. candidate at Carnegie Mellon. "All the information in the game is available for both sides to see. Poker is a game of imperfect information, since neither player can see their opponent's cards," he writes in an email to The Christian Science Monitor.

Carnegie Mellon's No-Limit Texas Hold'em software made short work of four of the world's best professional poker players in Pittsburgh at the grueling "Brains vs. Artificial Intelligence" poker tournament. Poker now joins chess, Jeopardy, go, and many other games at which programs outplay people. But poker is different from all the others in one big way: players have to guess based on partial, or "imperfect" information. One of the most annoying things about Android has long been the custom skins that manufacturers would slap on top of the operating system. Things have gotten better in recent years, but plenty of users would be happier using Android as Google intended.

People generally appreciate how the new wave of artificial intelligence-powered chatbots from Web giants can perform basic online tasks on our behalf. Who doesn't like having the ability to order a large pepperoni pizza by speaking five words into a smartphone? But security experts warn there's not much to stop cybercriminals from using AI technology to take social engineering hacks and identity theft to scary new levels. A dire warning about the increasing use of AI technology by cybercriminal was issued by Intel (NASDAQ: INTC) last month. Eric Peterson, a Director of Threat Research at Intel Security, warned that machine learning is starting to crop up in sophisticated scams that have already netted $3 billion for the bad guys.

In a world that operates on billions of digits every day, humans are too slow and inattentive. To adapt, we must automate the processing of millions of complex transactions on a daily basis, at speeds fast enough to satisfy impatient digital users. This adaptation requires a massive level of digital transformation that can support operations, business processes and decision-making speeds faster than is humanly possible. Historically, digital technologies get faster, cheaper, more powerful and smaller every couple of years. We operate in human time, a biological cadence influenced by the physical environment, our well-documented physical, mental and emotional limitations, and the universe that we live in.

For generations, computers that have the ability to think for themselves have been the stuff of science fiction. Neural networks could provide computers with the ability to identify objects and solve problems. However, scientists can't figure out why the computer reaches the conclusion it does. How can we make computers explain themselves? While computers are currently not self-aware, there are programs and algorithms that enable computers to learn and behave in a similar manner to the human brain. Neural networks are used to teach computers how to identify objects, recognize patterns, and even solve problems by feeding in stimuli, recording the output, and then feeding back a result (whether correct or not).

Great idea, big potential, but few applications so far and a lot to learn. This sums up the outlook for how public services could make use of artificial intelligence (AI), the technology that is stirring up hopes and fears, and is already surrounded by an aura of inevitability. There is some debate about its definition, but it is generally seen as a stream of computing developed to carry out tasks usually requiring human intelligence, and to learn from what it takes in. It came in for a new round of attention last week when the Government's chief scientific adviser, Sir Mark Walport, delivered a Turing Institute lecture on the potential. It was notable for emphasising the overall significance rather than much precision on how AI could be used: Walport spoke of applications in justice, welfare, education and medicine, but largely in broad terms.

Google releases massive visual databases for machine learning Using the Bizarro Pipe to Debug magrittr Pipelines in R 26 Great Articles and Tutorials about Regression Analysis 25 Big Data Terms You Must Know To Impress Your Date Journey Science in Telecom: Take Customer Experience to the Next Le... Importance of Hypothesis Testing in Quality Management Are typos and small mistakes making your business data inaccurate? Journey Science in Telecom: Take Customer Experience to the Next Le... Are typos and small mistakes making your business data inaccurate?

Stanford researchers are leveraging GPU-based machines in the Amazon EC2 cloud to run deep learning workloads with the goal of improving diagnostics for a chronic eye disease, called diabetic retinopathy. The disease is a complication of diabetes that can lead to blindness if blood sugar is poorly controlled. It affects about 45 percent of diabetics and 100 million people worldwide, many in developing nations. Final-year Stanford PhD students Apaar Sadhwani and Jason Su got involved in developing the diagnostic solution as part of a class project and corresponding Kaggle competition that was held last year. Sponsor Amazon provided AWS cloud credits in support of the research.

We brought Alexa into our home three months ago with Amazon Echo. Stumping her was our simple pleasure for a couple days. Soon after, we forgot Alexa was there. She became one of our many mute appliances. A month and a half later, however, Alexa came alive of her own accord.

Versace may be linked to high-fashion, but one family member wants the name to also be associated with artificial intelligence and robots. Massimiliano Versace, second cousin to Versace Group vice president Donatella Versace and to the Italian fashion company's late founder, Gianni Versace, is CEO of the Boston-based artificial intelligence startup Neurala. Whereas many of his relatives chose careers in luxury apparel, Versace wanted to pursue science and technology. "They make clothes and I make artificial brains for drones," Versace said. Versace's startup, which on Tuesday said it had landed a $14 million investment round led by Pelion Ventures, specializes in a type of artificial intelligence called deep learning.