After Thursday's annual shareholder meeting in downtown Los Angeles, LA Times' parent Tribune Publishing announced it would be changing its name to tronc Inc. and moving its shares from the New York Stock Exchange to the Nasdaq, effective June 20. In the release, the future consonant-heavy media organization describes itself as a "a content curation and monetization company focused on creating and distributing premium, verified content across all channels," or a news organization, in other words. It also "plans to launch www.tronc.com, "Our industry requires an innovative approach and a fundamentally different way of operating," Ferro said in the release. Earlier in the day, Tribune Chairman Michael Ferro won a big victory when he had his slate of board members confirmed.

This blog post will provide an introduction into using machine learning algorithms with InsightEdge. We will go through an exercise to predict mobile advertisement click-through rate with Avazu's dataset. There are several compensation models in online advertising industry, probably the most notable is CPC (Cost Per Click), in which an advertiser pays a publisher when the ad is clicked. Search engine advertising is one of the most popular forms of CPC. It allows advertisers to bid for ad placement in a search engine's sponsored links when someone searches on a keyword that is related to their business offering.

It is obvious that we are living in a data deluge era, evidenced by the phenomenon that enormous amount of data have been being continually generated at unprecedented and ever increasing scales. Large-scale data sets are collected and studied in numerous domains, from engineering sciences to social networks, commerce, biomolecular research, and security [1]. Particularly, digital data, generated from a variety of digital devices, are growing at astonishing rates. According to [2], in 2011, digital information has grown nine times in volume in just 5 years and its amount in the world will reach 35 trillion gigabytes by 2020 [3]. Therefore, the term "Big Data" was coined to capture the profound meaning of this data explosion trend. To clarify what the big data refers to, several good surveys have been presented recently and each of them views the big data from different perspectives, including challenges and opportunities [4], background and research status [5], and analytics platforms [6].

Artificial intelligence (AI) and robots in the technology sector are some of the emerging trends of the century, spearheading a revolution where workers may soon be replaced by robots and automated systems. Disney is already jumping into the world of robotics through projects developing at Disney Research, a global network of research labs working on a variety of innovative technologies and automated systems. One of the most recent productions is a set of robotic arms that mimic human movement. Here's a closer look at some of the latest developments in the field of robotics, and what the future may hold for both consumers and companies as AI and robots become more commonplace: Technology that Mimics Human Movement One of the most interesting projects underway at Disney Research labs is a camera-mounted robot named'Jimmy'. This particular robot is designed to stream video content to an operator that is wearing a virtual reality headset.

The University of Washington will be hosting the first of four White House Office of Science and Technology Policy workshops on artificial intelligence. The session in Seattle on Tuesday, involving the UW School of Law and the UW Tech Policy Lab, will focus on legal and policy issues around artificial intelligence. Speakers include UW professors, White House staff and the chief executive officer of the Allen Institute for Artificial Intelligence. Oren Etzioni, who is also a UW computer science and engineering professor, will provide an overview on the current state of artificial intelligence, followed by two panel discussions. The first will examine issues around making decisions in the private or public sector using artificial intelligence.

When Bob Greifeld became Nasdaq's CEO in 2003, he was presented with outdated tools and a company that was bleeding cash and rapidly losing market share. Thirteen years later, Nasdaq has the largest market share for options and equities of any exchange in the US. Through acquisitions and partnerships, Greifeld has shaped Nasdaq into what he primarily views as a cutting-edge technology company. During a recent interview with Business Insider, Greifeld discussed his vision for the future of Nasdaq and how it fits into the exchange industry. What follows is that portion of our interview, edited for length and clarity.

When Bob Greifeld became Nasdaq's CEO in 2003, he was presented with outdated tools and a company that was bleeding cash and rapidly losing market share. Thirteen years later, Nasdaq has the largest market share for options and equities of any exchange in the US. Through acquisitions and partnerships, Greifeld has shaped Nasdaq into what he primarily views as a cutting-edge technology company. During a recent interview with Business Insider, Greifeld discussed his vision for the future of Nasdaq and how it fits into the exchange industry. What follows is that portion of our interview, edited for length and clarity.

From self-driving vehicles to social robots, artificial intelligence is evolving at a rapid pace, creating vast opportunities as well as complex challenges. Recognizing that, the White House Office of Science and Technology Policy is co-hosting four public workshops on artificial intelligence -- the first of them May 24 at the University of Washington. Subsequent events will take place in Washington, D.C.; in Pittsburgh, Pennsylvania; and in New York City. Put on by the UW School of Law and the UW Tech Policy Lab, the session will focus on legal and policy issues around artificial intelligence, or AI. Etzioni will provide an overview on the current state of artificial intelligence, followed by two panel discussions.

The growing importance of business intelligence and data analytics applications in driving business decision making has made data integration's vital role in the enterprise crystal clear. From gathering data, transforming it into useful information and delivering it to the business users or processes that need it, data integration routines provide the crucial link between a variety of source and target systems. As the first article in this series examined, several types of packaged software have emerged to meet the challenges of data integration. The current generation of data integration tools consists of full-fledged suites that support extract, transform and load (ETL) processes, application integration, cloud-based and real-time integration, data virtualization, data cleansing and data profiling. How can you determine if your organization should invest in a data integration tool?

Apple's unprecedented decision to throw 1 billion into a Chinese ride-hailing firm last week may seem like a head-scratcher. And why not invest that money here in the United States? But this move was no accident. Not only is it a sign of Apple's growing interest in transportation -- a rapidly changing industry, thanks to groundbreaking technologies such as automation -- but it is also a bet on a country that wants to zip past the United States in the development of the cars of the future. China has moved with surprising speed to prepare for the next generation of automotive technology.