In 2017, a poker bot called Libratus made headlines when it roundly defeated four top human players at no-limit Texas Hold'Em. Now, Libratus's technology is being adapted to take on opponents of a different kind--in service of the US military. Libratus--Latin for balanced--was created by researchers from Carnegie Mellon University to test ideas for automated decision-making based on game theory. Early last year, the professor who led the project, Tuomas Sandholm, founded a startup called Strategy Robot to adapt his lab's game-playing technology for government use, such as in wargames and simulations used to explore military strategy and planning. Late in August, public records show, the company received a two-year contract of up to $10 million with the US Army.

If you'll permit me a sweeping generalization or two, I will say that most of us home cooks, deep down, would love to be able to confidently unveil a dazzling dessert at the end of a dinner party or holiday feast. For the joy it brings our loved ones, for their warm admiration, for the reinforcement that we can do anything we want in the kitchen, and in life. And almost precisely that same number of home cooks feels a little shaky about pulling it off. Heck, especially me, because I had to go and write a cookbook about Genius Desserts and now the expectations of my well-intentioned family and friends weigh a little heavier. For all of us, a dessert that will look and taste spectacular no matter what your sidetracked mind might do is a gift, and we should hold it tightly.

As a data science engineer, I found one of the most challenging task is Text Analytics. Natural language processing is one the cutting edge technology to talk with computers .

One question I get fairly often from folks who are just getting into NLP is how to evaluate systems when the output of that system is text, rather than some sort of classification of the input text. These types of problems, where you put some text into your model and get some other text out of it, are known as sequence to sequence or string transduction problems. This sort of technology is right out of science fiction. With such a wide range of exciting applications, it's easy to see why sequence to sequence modeling is more popular than ever. What's not easy is actually evaluating these systems. Unfortunately for folks who are just getting started, there's no simple answer about what metric you should use to evaluate your model.

MUMBAI: Private equity firm Apax Partners has signed a definitive agreement to invest as much as $200 million to become the single largest shareholder in Fractal Analytics, India's second largest big data firm. The transaction, which consists of a secondary stake acquired from existing shareholders such as Malayasian sovereign investor of Khazanah and T.A. Associates besides a primary investment into the business, both the companies said in a statement. Though not disclosed, sources tell ET, Apax will end up with a significant minority stake of around 45%. The deal is expected to get closed by February 2019, the statement said. ET first reported about the potential transaction in its edition dated Jan 4. The company will use the investment by the Apax Funds to accelerate growth, both organically and through M&A, and to invest further in AI products and research.

One day, robots will take over and it's going to be "bad" to "very bad". According to a survey conducted by Oxford University's Center for the Governance of AI, many Americans fear a future where mechanisms of AI become too intelligent. When asked what kind of impact high-level machine intelligence would have on humanity, 34 percent of respondents thought it would be negative, with 12 percent going for the option "very bad, possibly human extinction". Only 27 percent of respondents believed in a positive outcome, 21 percent thought AI wouldn't change the future much and 18 percent said they didn't know what impact AI would have. When ask to consider a negative future outcome of AI technology, Americans ranked the AI apocalypse as more catastrophic than the possible failure to address climate change, even though respondents said that it was less likely to happen.

So much debate still rages about Artificial Intelligence (AI) and what it means for the future of society and humanity. While this continues, governments around the world are actively embracing the prospect of transforming their departments into smart digital governments that are able to deliver improved services to organisations and life-enhancing services to and resources to citizens who really need them. And do so in more collaborative, joined up ways that rely on sharing information and insights. Layer on the prospect of being able to do so at significantly lower cost and with greater operational efficiency; it's no wonder that the prospect of AI is irresistible. Rightly so, for we can already see just how disruptive a force AI has been in the commercial sector: in retail (with Alibaba and Amazon), in transport (with Uber), in entertainment (with Netflix) and thousands more applications.

The Consumer Electronic Show (CES) was full of artificial intelligence (AI) agents of change this past week. Amazon noted that 28,000 products are now partnered with Alexa, up from 4,000 this time last year. Distributing more content is a key focus of AI home devices, and Amazon, Google, Microsoft, and Samsung were all showcasing the AI-enabled life-enhancing features of their digital assistants. For this trend to continue, we need to embrace the policy challenges that AI brings to data collection and privacy. The explosion in AI products has been made possible by today's network speeds.

A significant use of AI not mentioned in this puff piece is the way that the Chinese are implementing surveillance technology in policing. While Pelley did ask about how Xi Jinping, the authoritarian leader of the Chinese government, might intend to use such technology for nefarious purposes, like targeting dissidents, Lee demured by saying that he couldn't read Xi's mind. Meanwhile, police near Beijing have been equipped with "smart" glasses. They use the same technology as Google glasses, which proved to be a commercial failure as a personal consumer good and are now being used by law enforcement. The Chinese are using these wearable pieces of technology to pick up facial features and car registration plates, which they then cross-check with a database of suspects in real time.

ABB's future of mining infographic shows how to drive profits World's largest flotation cells improve copper and molybdenum recovery in Mexico PRESS RELEASE: The solution will be released in early 2019 as part of MICROMINE's fleet management and mine control solution, Pitram. Using the processes of computer vision and deep machine learning, on-board cameras are placed on loaders to track variables such as loading time, hauling time, dumping time and travelling empty time. The video feed is processed on the Pitram vehicle computer edge device, the extracted information is then transferred to Pitram servers for processing and analyses. ABB's future of mining infographic shows how to drive profits World's largest flotation cells improve copper and molybdenum recovery in Mexico MICROMINE Chief Technology Officer Ivan Zelina explained the solution intelligently considered the information gathered to pinpoint areas of potential improvement that could bolster machinery efficiency and safety. "Pitram's new offering takes loading and haulage automation in underground mines to a new level," Mr Zelina said.