Don't be alarmed, but a computer just beat 11 professional poker players in a 3,000 hand match of the incredibly complex Texas Hold'em, using'intuition'. DeepStack is the first computer programme to outplay humans at the game, which it played over a period of four weeks. Card players tend to rely on microexpressions – tiny subconscious flashes of emotion across the face that last no longer than a quarter of a second. The computer, which was developed by scientists at the University of Alberta, Charles University in Prague and Czech Technical University, honed its'intuition' through deep learning – allowing it to reassess its strategy with each move. Professor Michael Bowling, from Alberta, said: 'Poker has been a longstanding challenge problem in artificial intelligence.

If the popular media are to be believed, artificial intelligence (AI) is coming to steal your job and threaten life as we know it. If we do not prepare now, we may face a future where AI runs free and dominates humans in society. The AI revolution is indeed underway. To ensure you are prepared to make it through the times ahead, we've created a handy survival guide for you. The first step in every conflict is knowing your target.

As excitement (and panic) about the opportunities and threats of emerging technologies spreads into boardrooms across the world, it is worth considering that it is not just the technologies themselves which are disruptive. Indeed the bursting of the tech bubble in 2000 taught us that the technologies themselves are vulnerable to issues of scaling and adoption. Furthermore, of the key emerging technologies we have identified: 3D Printing, Advanced Robotics, Artificial Intelligence, Internet of Things and Virtual Reality, some of them have been around in some shape or form for some time. What is different now to 2000, and means the impact of technology is truly disruptive on a large and wide scale, is that we now have the business model enablers to drive the technology through a business. These business model enablers mean we now have access to the funding, platforms, processing power, software, and data to turn the technology into useful, scalable solutions.

LOS ANGELES As shares of California-based Snap Inc began trading on the New York Stock Exchange on Thursday, two dozen residents of the company's adopted home of Venice Beach protested outside its offices, accusing the growing tech company of spoiling their seaside community.

Kaplan Professional has announced it acquired an artificial intelligence company in an effort to create new tools for financial advisers amid a changing environment. In a new announcement yesterday, Kaplan said it has now acquired Red Marker. Kaplan Australia and New Zealand managing director Rob Regan said the acquisition would enable Kaplan to broaden its compliance solutions to the financial services sector through artificial intelligence. "We are investing in real-time learning with the aim of further equipping advisers with the tools they need to maximise their success in a rapidly changing landscape," he said. "By enabling advisers to confidently embrace compliance, it will allow them to continually increase their knowledge in a reportable manner. "Adding Red Marker to the Kaplan portfolio will accelerate the development of personalised and adaptive learning engines in the financial services sector." Red Marker principals and staff will continue with the business, the statement said. Red Marker managing director Matt Symons said, "Our clients are really enthusiastic about Artemis.

The idea to use artificial intelligence in bridge engineering process is very old. Since the 1950s studies on AI applications in civil or bridge engineering have proliferated. Most of these studies have dealt with specialized isolated engineering subtasks. Few of the applications have been delivered to practitioners and were used to advance their work. The decision to commission or replace an old bridge draws upon many economical, political and cultural issues. These issues determine much of the overall context in which a new bridge project is situated.

It makes sense for large technology companies like Google and Microsoft to open source AI and machine learning solutions because they have overlapping vertical interests in providing vast cloud services. These come into play when a certain machine learning library becomes popular and users deploy it on the cloud and so forth. It is less clear why financial services companies, which play a much more directly correlated zero sum game, would open up code that they paid the engineering team to create. It's interesting that hedge funds, traditionally thought to be the most secretive of financial institutions, have been proactive in pushing an open source software agenda. AQR Capital Management was probably patient zero when it came to opening up their code around data storage – and this move, shepherded by software engineer Wes McKinney, kickstarted the popular Pandas libraries project.

The truth is that "artificial intelligence" is a broad term that refers to much more than what has been popularized in pop culture... and it's a branch of science that will have irreversible impact on the marketing world. Before we get into how, here is a short glossary of terms and some background information that will help you get the most out of this issue. A way of talking about the algorithms that computers use to build their own models based on example input. It describes a computer that can move beyond fully descripted code and learn from experience, just as humans do. Deep learning is also sometimes known as neural networks.

After building up the human component of their network of suicide prevention organizations, Facebook is now bringing in the machines: The social media company announced they have updated their suicide prevention tools with artificial intelligence to identification of those at risk as well as improve the reporting process and speed up response time. On a company blog post from Vanessa Callison-Burch, Jennifer Guadagno and Antigone Davis (Facebook's Product Manager, Researcher, and Head of Global Safety, respectively) described key features of the updates, which include the integration of their prevention tools with Facebook Live and a testing phase of AI-powered pattern recognition to identify posts likely to include thoughts of suicide. "Based on feedback from experts, we are testing a streamlined reporting process using pattern recognition in posts previously reported for suicide," the company stated. "This artificial intelligence approach will make the option to report a post about'suicide or self injury' more prominent for potentially concerning posts like these." As Facebook tests that tool, employees will review posts flagged by the software and provide resources if the situation calls for it, even if no one has reported the post yet.

MAOS-TSP [1] is a multiagent optimization system (MAOS) for solving the Traveling Salesman Problem (TSP). The source code can be downloaded here. Related Information: Please find other related code and software in our Source Code Library. License Information: You can redistribute it and/or modify it under the terms of the Creative Commons Non-Commercial License 3.0. System Requirements: MAOS-TSP is a platform-independent software developed by JAVA version 1.5 or above.