The scheme debuted last year with eight companies, but this year's event (of which TTG is media partner) is set to feature 15 contenders – of which five will be shortlisted to compete for a chance to win the 2017 Travel Technology Disrupt Award, as well as a coveted free stand at next year's show. "We're excited to give double the amount of support to start-ups through Launchpad in 2017," said Sam Cande, group commercial director, Business Travel Show – which takes places over the same dates on the ground floor of London's Olympia on February 22-23. "The show has a history of introducing buyers to innovation, so it means a lot that, by supporting these start-ups, we're truly helping them excel and drive the industry forward." Attendees can experience the rise of the robots, but not the demise of the human race (not just yet, anyway) from 12.30-1.10pm As well as nurturing the travel technology companies of tomorrow, TTE will be playing host to a range of exhibitors, as well as debates, keynotes and seminars.

Humanity has finally folded under the relentless pressure of an artificial intelligence named Libratus in a historic poker tournament loss. As poker pro Jason Les played his last hand and leaned back from the computer screen, he ventured a half-hearted joke about the anticlimactic ending and the lack of sparklers. Then he paused in a moment of reflection. Libratus lived up to its "balanced but forceful" Latin name by becoming the first AI to beat professional poker players at heads-up, no-limit Texas Hold'em. The tournament was held at the Rivers Casino in Pittsburgh from 11-30 January.

Antarctica - After 12 hours breaking through pack ice, passing groups of penguins and seals on the ice flow, and tracked by pods of Minke whales, we arrive at the edge of the great southern continent. This part of the Antarctic coastline is the windiest place on the planet at sea level and, as we pull alongside the towering ice cliffs in the Russian research ship Akademik Treshnikov, we are whipped and buffeted by their ferocity. The following morning the wind has abated and with blue skies and sunshine, the same giant ice cliffs have a meringue-like appearance. These walls of ice are the edges of glaciers, which stretch more than 40km from land out over the ocean. Cracked and crevassed, chunks of ice periodically "calve" from these glaciers, forming icebergs that are driven offshore by wind and current.

Automation is happening, and it will bring substantial benefits to businesses and economies worldwide, but it won't arrive overnight. A new McKinsey Global Institute report finds realizing automation's full potential requires people and technology to work hand in hand. Recent developments in robotics, artificial intelligence, and machine learning have put us on the cusp of a new automation age. Robots and computers can not only perform a range of routine physical work activities better and more cheaply than humans, but they are also increasingly capable of accomplishing activities that include cognitive capabilities once considered too difficult to automate successfully, such as making tacit judgments, sensing emotion, or even driving. Automation will change the daily work activities of everyone, from miners and landscapers to commercial bankers, fashion designers, welders, and CEOs. But how quickly will these automation technologies become a reality in the workplace?

Machine learning has long powered many products we interact with daily–from "intelligent" assistants like Apple's Siri and Google Now, to recommendation engines like Amazon's that suggest new products to buy, to the ad ranking systems used by Google and Facebook. More recently, machine learning has entered the public consciousness because of advances in "deep learning"–these include AlphaGo's defeat of Go grandmaster Lee Sedol and impressive new products around image recognition and machine translation. In this series, we'll give an introduction to some powerful but generally applicable techniques in machine learning. These include deep learning but also more traditional methods that are often all the modern business needs. After reading the articles in the series, you should have the knowledge necessary to embark on concrete machine learning experiments in a variety of areas on your own.

Artificial neural networks provide us incredibly powerful tools in machine learning that are useful for a variety of tasks ranging from image classification to voice translation. So what is all the deep learning rage about? The media seems to be all over the newest neural network research of the DeepMind company that was recently acquired by Google. They used neural networks to create algorithms that are able to play Atari games, learn them like a human would, eventually achieving superhuman performance. Deep learning means that we use artificial neural network with multiple layers, making it even more powerful for more difficult tasks.

Cyber threats are an ever-present danger to global economies and are projected to surpass the trillion dollar mark in damages within the next year. As a result, the cybersecurity industry is investing heavily in machine learning in hopes of providing a more dynamic deterrent. ABI Research forecasts machine learning in cybersecurity will boost big data, intelligence, and analytics spending to $96 billion by 2021. "We are in the midst of an artificial intelligence security revolution," says Dimitrios Pavlakis, Industry Analyst at ABI Research. "This will drive machine learning solutions to soon emerge as the new norm beyond Security Information and Event Management, or SIEM, and ultimately displace a large portion of traditional AV, heuristics, and signature-based systems within the next five years."

Whether we search for recipes, chatting with friends or pay via the web, we create massive amounts of data. Clever use of this information forms the basis for future digital services. With the development of Internet of things and artificial intelligence, the amount of data will increase dramatically, and this data is considered as the raw material in the digital economy. The value attached to mobile payments are not necessarily transactional revenue, but ownership of customer data. A report by Deutsche Bank confirms this and shows that innovation in mobile payments will open up for new products based on customer data.

Beyond the two-dimensional focus on graphics and the three-dimensional focus on products, we're now in an era where designers are increasingly focusing on time and space, guided by technological advances in artificial intelligence, robotics, and smart environments. While great thinkers like Dieter Rams and George Nelson offered their own design principles in past eras, industrial designer Yves Béhar points out that there are no comparable manifestos or guidelines for designers working with AI, robotics, and connected technology today. Last week, in a talk delivered at the inaugural A/D/O/ Design Festival in Brooklyn, Béhar presented his vision for what those guidelines should look like--in the form of 10 principles for design in the age of AI. What problem are you trying to solve with AI? Considering the multitude of "smart" products that are actually quite stupid, it's a question worth asking. "At CES there was a lot of mundane automation that is more part of what I would call gadgetry--versus automation that truly improves people's lives or delivers considerable amounts of service or value," Béhar says.

These numbers are good enough to make any experienced customer support executive cringe! As alarming as it can be, it is an idea that needs to be well thought out before implementation. So to get you up to speed, in this article, we have compiled everything that you need to know before making the bold move of merging Artificial Intelligence (AI) with your existing customer support system. As an add on, we have also mentioned some of the best AI based support solutions available in the market. First, let's find out why AI is emerging as a crucial technology in providing customer support.