Call it a "Forrest Gump moment;" an instance of being in the right place at the right time for no other reason than just plain luck. A "Forrest Gump moment" is based upon Tom Hanks' character in the movie "Forrest Gump," a guy who always seemed to be in the right place at the right time meeting Presidents Kennedy, Johnson and Nixon at critical points in American history. I too have had a Forrest Gump moment in meeting President Reagan, however, my deeper Forrest Gump moments have been my long association with the history of analytics. I was fortunate to be at the birth of the Business Intelligence and Data Warehouse era while working for Metaphor Computers to deploy Decision Support Systems across Procter & Gamble in the late 1980's. And was fortunate again in the late 2000's to be at the launch of the Data Science era while building Advertiser Analytics at Yahoo.

Episode 106 - Edward Hess discusses The New Smart Machine Age and where humans fit into the convergence of business, technology and automation. Will smart machines and robots start taking our jobs? What can we do...us humans...to prepare for the inevitable transformation? Ed is a Professor of Business Administration and Batten Executive-in-Residence at the Darden Graduate School of Business at the University of Virginia. You've seen and heard him in places like WSJ Radio, CNBC, NPR, and Investor's Business Daily, among many others.

Music and Machine Learning- sounds not so musical? Just like everywhere, Artificial Intelligence has also pervaded the world of music. Spotify, Grooveshark, Pandora, and others can today recommend music based on our listening habits and moods. What does this mean for the music industry? Will AI take away jobs in the industry?

Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention. In this paper we focus on the construction of taxonomies for fictional domains, using noisy category systems from fan wikis or text extraction as input. Such fictional domains are archetypes of entity universes that are poorly covered by Wikipedia, such as also enterprise-specific knowledge bases or highly specialized verticals. Our fiction-targeted approach, called TiFi, consists of three phases: (i) category cleaning, by identifying candidate categories that truly represent classes in the domain of interest, (ii) edge cleaning, by selecting subcategory relationships that correspond to class subsumption, and (iii) top-level construction, by mapping classes onto a subset of high-level WordNet categories. A comprehensive evaluation shows that TiFi is able to construct taxonomies for a diverse range of fictional domains such as Lord of the Rings, The Simpsons or Greek Mythology with very high precision and that it outperforms state-of-the-art baselines for taxonomy induction by a substantial margin.

Social media communications are becoming increasingly prevalent; some useful, some false, whether unwittingly or maliciously. An increasing number of rumours daily flood the social networks. Determining their veracity in an autonomous way is a very active and challenging field of research, with a variety of methods proposed. However, most of the models rely on determining the constituent messages' stance towards the rumour, a feature known as the "wisdom of the crowd". Although several supervised machine-learning approaches have been proposed to tackle the message stance classification problem, these have numerous shortcomings. In this paper we argue that semi-supervised learning is more effective than supervised models and use two graph-based methods to demonstrate it. This is not only in terms of classification accuracy, but equally important, in terms of speed and scalability. We use the Label Propagation and Label Spreading algorithms and run experiments on a dataset of 72 rumours and hundreds of thousands messages collected from Twitter. We compare our results on two available datasets to the state-of-the-art to demonstrate our algorithms' performance regarding accuracy, speed and scalability for real-time applications.

This story forms part of a collaboration with Dazed Digital -- where pop culture meets the underground. The opinions expressed in this article belong to each individual author. Technology is advancing at such a fast rate right now that it can feel like we are well on our way to a robot apocalypse. But, if we closely observe how artists are harnessing artificial intelligence in ways that push humanity forward, we can see that our fears of a technological dystopia might never actualize. From using AI to create new and innovative genres in music, to new takes on classical nudes, and innovative ways to track anonymous warfare, art's relationship to AI right now is illuminating humanity's strength.

If you see a video of a politician speaking words he never would utter, or a Hollywood star improbably appearing in a cheap adult movie, don't adjust your television set -- you may just be witnessing the future of'fake news.' 'Deepfake' videos that manipulate reality are becoming more sophisticated due to advances in artificial intelligence, creating the potential for new kinds of misinformation with devastating consequences. As the technology advances, worries are growing about how deepfakes can be used for nefarious purposes by hackers or state actors. Paul Scharre of the Center for a New American Security looks at a'deepfake' video of former US President Barack Obama manipulated to show him speaking words from actor Jordan Peele on January 24, 2019, in Washington'We're not quite to the stage where we are seeing deepfakes weaponized, but that moment is coming,' Robert Chesney, a University of Texas law professor who has researched the topic, told AFP. Chesney argues that deepfakes could add to the current turmoil over disinformation and influence operations. 'A well-timed and thoughtfully scripted deepfake or series of deepfakes could tip an election, spark violence in a city primed for civil unrest, bolster insurgent narratives about an enemy's supposed atrocities, or exacerbate political divisions in a society,' Chesney and University of Maryland professor Danielle Citron said in a blog post for the Council on Foreign Relations.

In a nutshell, we aim to generate polyphonic music of multiple tracks. The proposed models are able to generate music either from scratch, or by accompanying a track given a priori by the user. We train the model with training data collected from Lakh Pianoroll Dataset to generate pop song phrases consisting of bass, drums, guitar, piano and strings tracks. Run the following command to set up a new experiment with default settings. This article was summarized automatically with AI / Article-Σ / BuildR BOT .

Elon Musk has sounded off on AI various times, and how it can pose a massive threat to the world. At a meeting of the nation's governors, Elon Musk warned that artificial intelligence was "the greatest risk we face as a civilization". As a result of his deep involvement in the tech industry, Elon Musk said he "[has] access to the very most cutting edge AI," and that "people should be really concerned about it." In a tweet, Elon Musk stated that AI was "potentially more dangerous than nukes". Elon Musk is also concerned that AI can be used in a warfare scenario, by being able to create massive amounts of fake news (i.e. in a propaganda scheme to push a certain ideology), fake press releases, and manipulating information in general.

A hitchhiking robot was beheaded in Philadelphia. A security robot was punched to the ground in Silicon Valley. Another security bot, in San Francisco, was covered in a tarp and smeared with barbecue sauce. Why do people lash out at robots, particularly those built to resemble humans? It is a global phenomenon. In a mall in Osaka, Japan, three boys beat a humanoid robot with all their strength. In Moscow, a man attacked a teaching robot named Alantim with a baseball bat, kicking it to the ground, while the robot pleaded for help.