Have you ever considered what real people actually do with the products of all of the innovation flowing from the IT industry? Sometimes, the answers are quite obvious. Shopify (NYSE:SHOP) essentially builds websites for mainly smaller businesses and facilitates credit card transactions. Silver Spring Networks (NYSE:SSNI) uses the technology of the IoT to facilitate the "intelligent city" and the "smart grid." Salesforce (NYSE:CRM) sells solutions that help companies manage both their sales people or agents and manage their customer interactions. Those and other solution sets are sold to rather obvious customers. But who actually buys and uses Big Data Appliances or Artificial Intelligence or advanced analytics. But in recent years, some financial services firms have tried to transform themselves from their roots as the providers of simple financial products used by consumers and business into what is known these days as Fintech. There are more than few such companies and perhaps at this point, there are companies with more aspirations as opposed to significant revenue. Equifax (NYSE:EFX) for many years has been known as one of the 3 major credit reporting agencies, the people who calculated your credit score using some arcane methodology. The business of selling credit scores to both business and consumers is hardly the most exciting in the world and has modest growth organic growth prospects in the US.

At WebRTC Argentina we covered a number of topics, including an introduction to WebRTC with coding demonstrations, demos of WebRTC use cases, and design/UX for WebRTC. We concluded the mini-conference with this talk, where we wanted to stretch people's minds a little bit about WebRTC. WebRTC is not simply about 1-1 video chats or business conferencing tools. WebRTC can be one part of larger technological change in our society, and in this talk we give updates on WebRTC in the short term as well as one vision for how WebRTC and Artificial Intelligence may intersect in the future. You can see the complete presentation below, and we've included the transcript below the video.

The workshop program at the Eleventh Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment was held November 14–15, 2015 at the University of California, Santa Cruz, USA. The program included 4 workshops (one of which was a joint workshop): Artificial Intelligence in Adversarial Real-Time Games, Experimental AI in Games, Intelligent Narrative Technologies and Social Believability in Games, and Player Modeling. This article contains the reports of three of the four workshops.

Civil unrest events (protests, strikes, and “occupy” events) are common occurrences in both democracies and authoritarian regimes. The study of civil unrest is a key topic for political scientists as it helps capture an important mechanism by which citizenry express themselves. In countries where civil unrest is lawful, qualitative analysis has revealed that more than 75 percent of the protests are planned, organized, or announced in advance; therefore detecting references to future planned events in relevant news and social media is a direct way to develop a protest forecasting system. We report on a system for doing that in this article. It uses a combination of keyphrase learning to identify what to look for, probabilistic soft logic to reason about location occurrences in extracted results, and time normalization to resolve future time mentions. We illustrate the application of our system to 10 countries in Latin America: Argentina, Brazil, Chile, Colombia, Ecuador, El Salvador, Mexico, Paraguay, Uruguay, and Venezuela. Results demonstrate our successes in capturing significant societal unrest in these countries with an average lead time of 4.08 days. We also study the selective superiorities of news media versus social media (Twitter, Facebook) to identify relevant trade-offs.

The 2015 conference continued the tradition with a selection of 6 deployed applications describing systems in use by their intended end users, 13 emerging applications describing works in progress, and three papers in a new category for challenge problems. In the first article, Activity Planning for a Lunar Orbital Mission, John Bresina describes a deployed application of current planning technology in the context of a NASA mission called LADEE (Lunar Atmospheric and Dust Environment Explorer). Bresina presents an approach taken to reduce the complexity of the activity-planning task in order to perform it effectively under the time pressures imposed by the mission requirements. One key aspect of this approach is the design of the activity-planning process based on principles of problem decomposition and planning abstraction levels. The second key aspect is the mixed-initiative system developed for this task, the LADEE activity scheduling system (LASS). The primary challenge for LASS was representing and managing the science constraints that were tied to key points in the spacecraft's orbit, given their dynamic nature due to the continually updated orbit determination solution. In our second article, Helping Novices Avoid the Hazards of Data: Leveraging Ontologies to Improve Model Generalization Automatically with Online Data Source, Sasin Janpuangtong and Dylan Shell describe an emerging application of an endto-end learning framework for large-scale data analytics that allows a novice to create models from data easily by helping structure the model-building process.

Cannes Lions this year saw the ad industry expanding its creative capabilities. Over 13,500 delegates from about 90 countries descended on Cannes again this year hoping for a Lion in one of 17 categories. With awards honoring work from design to creative data to radio, the ceremonies reflected a complex industry drawing on a broader range of creative disciplines than in the past, but also facing unprecedented challenges in making campaigns work across channels. "There's never been so many channels or points of interactions, or agencies working on various parts of that," said Keith Weed, chief marketing and communications officer at Unilever. "It's important to make sure the brand experience does not get fragmented."

Not much is definitively proven about consciousness, the awareness of one's existence and surroundings, other than that its somehow linked to the brain. But theories as to how, exactly, grey matter generates consciousness are challenged when a fully-conscious man is found to be missing most of his brain. Several years ago, a 44-year-old Frenchman went to the hospital complaining of mild weakness in his left leg. It was discovered then that his skull was filled largely by fluid, leaving just a thin parameter of actual brain tissue. And yet the man was a married father of two and a civil servant with an IQ of 75, below-average in his intelligence but not mentally disabled.

Earlier this week, I found myself answering a question from a new colleague at Finning International that relates both to the research I do in the iSchool at the University of British Columbia, as well as the analytics, engineering & technology work that I lead at Finning. The questions were simple: 1) What is artificial intelligence? As I sat to reflect last evening, it dawned on me that taking time to craft a clear answer to these questions might be extremely beneficial for many. Analytics, data science, and predictive intelligence are hot topics in many communities and business areas. And yet, despite this interest, few folks I have talked to have a clear understanding of the history of the discipline; one, that frames much of the work currently going on within the space.

December's ICCV 2015 conference in Santiago, Chile has come and gone, but that's no reason not to know about its top papers. Get an update on which computer vision papers and researchers won awards.

Could Kevin Bacon have saved us from the 2008 financial crisis? But the network science behind six degrees of Kevin Bacon just well may have. According to the famous saying, every movie actor is separated from Kevin Bacon by six degrees of separation or less, going from co-star to co-star (actually most are separated from Bacon by only three degrees). Actors form a "small-world" network, meaning it takes a surprisingly small number of connections to get from any one member to any other. Natural and man-made small-world networks of all kinds are extremely common: The electric power grid of the western United States, the neural network of the nematode worm C. elegans, the Internet, protein and gene networks in biology, citations in scientific papers, and most social networks are small. Most of these small networks use hubs, or nodes with an especially large number of links to other nodes.