Artificial intelligence (AI), that is the ability of machines to imitate human intelligence processes, and machine learning, a branch of AI concerning the possibility for computers to learn when exposed to new information, are acquiring an increasingly important role in the travel industry and are expected to be among its main disruptors in the next few years. In particular, the huge amount of data collected by companies through the online and mobile channels from internal and external sources, the technological advancements in data analytics and the rise of AI agents, such as chatbots, are expected to drive significant changes in the way travel companies market their products, communicate with their customers and are able to assist them throughout the travel experience. Leading travel and technology companies, including among others, Google, Facebook, Expedia, Priceline, TripAdvisor and Airbnb, are currently working on the application of artificial intelligence and machine learning technologies to address the needs of their customers in a more efficient and customised way in order to increase conversions and loyalty. Artificial intelligence is at the heart of big data analytics used to predict customer behaviour and offer intelligent recommendations based on customers' preferences. Automated and instant analysis of the huge amount of data companies collect about their customers will mean in the next few years an increasingly personalised shopping experience for travel consumers, which at the same time will result in higher rates of conversions into sales and in a more productive shopping experience for consumers.

If you're still stuck on the same old on-page SEO routine, it's time to wake up, smell the coffee, and figure out what's up in 2016. If you're waking up from 2010, you've got a long way to go, Rip Van Winkle. But even if you're poking into the SEO world from just a few months ago, you might be surprised at how much changed while you were away. We're always in need of "updated" information for SEO, and I thought now was a great time to release my updated checklist. I've organized this list into three main sections: Analytics help you gain an insight into your visitor demographics and understand your marketing better.

One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology. "I really feel like I missed the mark in giving the correct amount of feedback," he wrote, pleading to revise an assignment. Thirteen minutes later, the TA responded. "Unfortunately, there is not a way to edit submitted feedback," wrote Jill Watson, one of nine assistants for the 300-plus students. Last week, Mr. Wilson found out he had been seeking guidance from a computer.

BEIJING – A Chinese government bureau is planning a base station for an advanced rescue ship in the disputed Spratly Islands, state media reported on Monday, as China continues its push to develop civilian and military infrastructure in the contentious region. The ship, which would carry drones and underwater robots, is set to be deployed in the second half of the year, said Chen Xingguang, political commissar of the ship, which is under the South China Sea Rescue Bureau of the Ministry of Transport, according to the official China Daily. The civilian bureau has 31 ships and four helicopters conducting rescue missions in the South China Sea, and officials from the department told the China Daily they work with the military on such efforts. Officials said the rescue ship base station would enable rescue forces to aid fishing boats in trouble, and shorten the distance they need to travel. It is unclear on which island the ship will be based, but China has carried out land reclamation and construction on several islands in the Spratly Archipelago, parts of which are also claimed by the Philippines, Vietnam, Brunei, Malaysia and Taiwan.

Welcome to a Meetup focused on the exciting possibilities that Machine Learning brings. We will give you a primer on the difference between supervised and unsupervised learning, common algorithms, frameworks and languages used for Machine Learning. We will also illustrate how Machine Learning and AI is used in the real world outside academia. Naturally, a hands-on lab is also on the agenda. We will provide an example to how you can approach a typical problem to be solved with Machine Learning.

IBM's California research lab sits atop a green hill, 15 miles south of downtown San Jose. There aren't any signs that suggest if you drive up the narrow road that wraps around the hill you'll find a research facility at the top. No signs that the research centre is home to a Fortune 500 company. No signs – even inside – that the company once dominated the personal computer industry. After decades in the spotlight as a hardware-centric firm selling PCs, servers and mainframes, the 105-year-old tech giant has made a dramatic shift into a realm that few understand: cognitive computing. Deep within the apps we use, the food we eat, the medicine we take, and the medical diagnoses we make, you'll find traces of IBM.

They don't want our jobs exactly, but work as we know it will be transformed nonetheless. So argues computer scientist Jerry Kaplan, who's been immersed in the intersection of technology, artificial intelligence and traditionally human tasks for nearly 40 years. The author of "Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence," Kaplan argues that huge changes are indeed underway -- they're just not the ones that are often discussed. First of all, "we don't automate jobs -- we automate tasks," Kaplan said during a mid-January discussion at Mitre organized by Hooks Book Events. And that process, he argued, has been underway since at least the Industrial Revolution.

Machine learning will give cars the ability to analyze and learn from hundreds of thousands, even millions, of driving situations to learn better than any human being can, Audi execs told the press at CES 2016 Wednesday. "In one year a 16-year-old driver might encounter 1,000 situations with a four-way stop," said Peter Steiner, managing director of Audi Electronics Venture. "But our systems will learn from hundreds of thousands, even millions, of such situations that can be stored, analyzed and improved from, so these cars can learn even better than a human being can." Audi is continuing to work toward fully autonomous vehicles -- it sent a self-piloted A7 sedan from San Francisco to Las Vegas in time for last year's CES -- even as it continues to introduce increasingly sophisticated advanced driver assistance features that have seen a strong uptake among Audi buyers. Audi continues to work closely with NVIDIA, incorporating our Tegra processors into its zFAS driver assistance control unit and MIB infotainment system.

Softbank Robotics, the creator of Pepper has announced its plan to hit Android this week. The company was in the limelight last year after the overwhelming response it received for a robot it launched in Japan. Aldebaran, a subsidiary of SoftBank, programmed that robot on its own customized OS, the NAOqi. Last night, at the Google I/O conference, the creators of that robot announced their plans to integrate it with Android. They will soon open development to the entire Android developers' community to facilitate greater variety, and customization in its functions.

Google is planning to put the art in artificial intelligence. The announcement was made at a session in Moogfest, a four-day music and technology festival in Durham, North Carolina. The company's artificial researcher Douglas Eck had developed a new group that would focus on figuring out what computers can truly create. The group is named Magenta, and they will launch more publicly at the start of June. However, the Moogfest attendees got an introduction on what it will be working on.