Chances are the entity managing your favorite smartphone app or Internet service isn't a person. Algorithms are setting the price of your airline ticket and hailing your Uber driver. And we're only at the beginning of a transition that is going to make the algorithms behind the software people interact with better able to understand and react to humans, technologists at a gathering of Seattle's burgeoning artificial-intelligence industry said Wednesday. "Every application that is going to get built, starting today and into the future, is going to be an intelligent app," said S. "Soma" Somasegar, a venture partner with Madrona Venture Group and a former Microsoft executive. The event, hosted by Somasegar's Seattle-based venture-capital firm, was held to highlight the cluster of companies in the region working on the cutting edge of intelligent software, including in the discipline dubbed machine learning.

Artificial intelligence (AI) is something of a buzz-phrase across the tech industry these days - but Microsoft's Dave Coplin says that it will come to have a profound impact on society as we know it. In his words, AI "will change everything". Coplin, the company's chief envisioning officer in the UK, was speaking a few days ago at an AI conference in London, where he described it as "the most important technology that anybody on the planet is working on today." "This technology will change how we relate to technology," he said. "It will change how we relate to each other. I would argue that it will even change how we perceive what it means to be human."

Sure, a NYC-based on-demand insurance app powered by artificial intelligence, launched with 2.6m in seed funding. Investors included ff Venture Capital, Montage Ventures, and Fosun Kinzon Capital (Fosun Group). Founded in late 2014, Sure offers individual accident, life, property, casualty, and warranty insurance policies on-demand and direct to consumers through their mobile devices. The platform uses a Robo-Broker driven approach to empower consumers with the ability to personalize their insurance needs via mobile based on location, context and behavior and eliminate the built-in limitations of the industry driven largely by not customized recommendations from brokers. The company is led by CEO and co-founder Wayne Slavin.

The New York Times has a lead article on collapsing US merger deals in 2016 so far. While last year set a record for the amount of money spent on corporate mergers -- 4.7 trillion -- this year is so far setting a very different record: the dollar amount of deals that have come undone, the famous paper writes. Since the beginning of January, 400 billion worth of corporate mergers have been withdrawn in the United States, almost three times the previous record for the same period, set in 2007, according to Dealogic, which analyzes such data. In the same paper, reporter John Markoff writes that the Pentagon is turning to Silicon Valley for the edge in Artificial Intelligence. On Wednesday, Secretary of Defense Ashton B. Carter made his fourth trip to the tech industry's heartland since being named to his post last year.

A couple of years ago, Andy Rubin--the celebrated creator of Android and until recently the head of Google's mobile Internet efforts--helped his wife, Rie, build a bakery in a decommissioned train station in Los Altos, California. They called it Voyageur du Temps, French for time traveler. As the name suggests, the bakery conveys visitors to an earlier era--by painstakingly re-creating the flavors and textures of classic European pastry. To pull this off, the Rubins went so far as to hire chefs from Japan, where traditional baking techniques are rigorously studied, and to purchase a rare Bongard Cervap oven, one of only two on the West Coast. The project was typical Rubin, in that it involved throwing an almost comical amount of money, energy, and engineering talent at a hobby, just for the fun of it. But it was also atypical Rubin, in that he usually marshals such resources to build artifacts from the future--like the robotic arm and the retinal scanner he's installed in his house. Even at his backward- looking bakery, Rubin couldn't resist adding some forward-leaning touches. He began writing software for a "closed cash" device that could receive payment, dole out change, and log transactions without a cashier's intervention. And he built a private meeting room in the back, complete with a homemade magnetized lock system.

Machine learning, a method of data analysis that automates analytical model building, is at the top of the "hype curve" for emerging technologies and is one of the top 10 strategic technology trends for 2016, according to Gartner. It's safe to say that most of us are already interacting with machine learning applications on a daily basis whether it's Apple's Siri, Facebook's face detection, Netflix personalized recommendations, or iOS's autocorrect. And from a business perspective, basically any organization that gathers data with the intention of acting on it can benefit from machine learning. But what can we learn from this growing trend? What can we do with such a widely applicable technology and how can we maximize its potential?

Automation and industrial robots have been in the manufacturing and related industries for decades, with the usage prevalent in shop floors and assembly lines. In 2008, a firm called Kiva Systems invented suitcase-like machines that would park underneath racks and move them around in the warehouse. Raffaello D' Andrea, the co-founder of Kiva, said: "You don't have to walk over to the shelves to get things -- the shelves come to you." Amazon acquired Kiva Systems four years later to obtain the technology to sort, organise and transport Amazon's massive inventory. Without a doubt, technology has reduced the need for human labour, especially in manual and routine tasks. It has largely done its job -- simplifying tasks and minimising errors -- although at the expense of eliminating low-skilled factory workers.

To maintain and build a Hi-tech military advantage, the Pentagon is turning to the country's software and technology hub, Silicon Valley and its hottest and latest technology Artificial Intelligence, popularly known as AI. Today, Ash Carter, Secretary of Defense made his fourth trip to the area since his appointment on the post in last year. He had been the frequent traveler of the region in the past as well, he said in his speech given at the Defense Department Research Facility near Google's headquarters. US, currently, is concerned with the re-emergence of China and Russia in the military powers and therefore is looking a unique and a better tool to make the military of the country strong and rigid. This plan was articulated as "Third offset" strategy by Carter at last fall.

Artificial intelligence (AI) is an emotionally loaded term that strikes fascination into some and fear into others. But if we strip it of fantasy and ignore cyborgs and apocalypse, there is a near-term, practical side of AI that is already unfolding. Most humans can recognise a chair because they have learnt what a chair is – they can identify thousands of examples of chairs even if they have never seen that chair before. Instead of memorising every image of what a chair could be, humans learn what a chair is and then apply that to new images and examples of chairs. But how does a computer learn what a chair is?

Amazon has suddenly made a remarkable entrance into the world of open-source software for deep learning. Yesterday the ecommerce company quietly released a library called DSSTNE on GitHub under an open-source Apache license. Deep learning involves training artificial neural networks on lots of data and then getting them to make inferences about new data. Several technology companies are doing it -- heck, it even got some air time recently in the show "Silicon Valley." And there are already several other deep learning frameworks to choose from, including Google's TensorFlow.