Robots are already putting a variety of jobs under threat from security guards to office managers, but soon they could be venturing into the sex industry too. Women and men could begin swapping human partners for androids within the next 10 years, according to predictions by a futurologist. Dr Ian Pearson, an inventor who has made a career out of predicting the future for PR firms, has produced a report on the future of sex. Sex with robots could soon replace human intimate relationships according to a recent report. It claims that intercourse with robots could overtake human intercourse by 2050.

Doing Data Science: A Kaggle Walkthrough Part 6 - Creating a Model Top Machine Learning Libraries for Javascript Improving Nudity Detection and NSFW Image Recognition History of Data Mining Predictive Analytics World in October: Government, Business, Financial, Healthcare Software 5 More Machine Learning Projects You Can No Longer Overlook BigDebug: Debugging Primitives for Interactive Big Data Processing in Spark Achieving End-to-end Security for Apache Spark with Databricks Predicting purchases at retail stores using HPE Vertica and Dataiku DSS Tutorials, Overviews, How-Tos Mining Twitter Data with Python Part 4: Rugby and Term Co-occurrences Ten Simple Rules for Effective Statistical Practice: An Overview Mining Twitter Data with Python Part 3: Term Frequencies Opinions The Big Data Ecosystem is Too Damn Big An Inside Update on Natural Language Processing From Research to Riches: Data Wrangling Lessons from Physical and Life Science News Top Stories, June 20-26: New Machine Learning Book, Free Draft Chapters; Machine Learning Trends & Future of A.I. Webcasts and Webinars Webinar, Jun 30: Introducing Anaconda Mosaic: Visualize. Bank of Ireland: Senior Data Scientist within the Advanced Analytics Team DuPont Pioneer: Data Scientist - Encirca Academic U. of Iowa: Business Analytics & Information Systems, Lecturer U. of Iowa: Lecturer: Business Analytics & Information Systems Top Tweets Top KDnuggets tweets, Jun 15-21: Predicting UEFA Euro2016; Visual Explanation of Backprop for Neural Nets Quote "Everything at scale in this world is going to be managed by algorithms and data ... every business will be an algorithmic business."

BOSTON, June 30, 2016 (GLOBE NEWSWIRE) -- indico, an innovator in the machine learning and artificial intelligence space, will make a presentation on deep learning at the Sentiment Analysis Symposium, which takes place in New York, July 12th. Dr. Daniel Kuster, a researcher at indico, will focus on the differences between deep learning and traditional machine learning approaches, and how the advantages of deep learning can be exploited to quickly gain new insights about what people say online, and how they say it. The presentation will take place at Fordham University's Lincoln Center Campus in New York City. Machine learning is becoming the tool of choice for analyzing text and image data. While traditional text processing solutions rely on the ability of experts to encode domain knowledge, machine learning models learn directly from the data.

German automaker BMW, which is already in that list, is likely to announce an expansion of its efforts Friday. The luxury vehicle maker will hold a joint press conference with technology companies Intel Corp. and Israel-based Mobileye. A press release issued by Intel late Wednesday said only that the "three companies have something exciting to share" during the Friday conference. Analysts widely expect the announcement of a collaborative effort to develop autonomous driving technology. A possible cooperation between the three companies would bring together a premium car manufacturer, one of the world's leading chip makers and a software company that specializes in driver assistance systems.

For many, the thought of playing board games evokes childhood memories of rainy-day Monopoly marathons or Scrabble showdowns. But board games are undergoing a modern renaissance. Players are seeking out a rare form of entertainment that doesn't involve staring at digital pixels, while game creators are tapping into online crowdfunding platforms like Kickstarter to finance their work. While the market remains minuscule compared to the 23.5 billion video game industry, sales of "hobby games" are up approximately 20% in 2015, according to one estimate. Among the foremost beneficiaries of the board gaming boom is Matthew Leacock.

Each year at Cannes Lions, the Saatchi & Saatchi New Directors' Showcase features a live show conceived around a theme that mirrors the most exciting happenings in the ad industry. This year it was less a live show, more an experiment. In a nod to the rising prominence of artificial intelligence, Saatchi & Saatchi and its LA agency Team One set about potential capabilities of the technology. The result is a music video that was creatively conceived, cast, directed, shot and edited wholly by machines. Saatchi & Saatchi hid it within the NDS reel and tasked the audience to try and pick it out among a crop of films by some of the world's most talented new directors.

Since taking office, President Obama has sent U.S. troops into action on land or in the skies of seven countries on two continents. Obama's administration has authorized Navy SEALs to kill Osama bin Laden in Pakistan and approved the fatal drone strike on an American cleric in Yemen. Here is a look at targeted killings under the Obama administration. Mansour was killed when a drone strike hit his vehicle as he traveled in Baluchistan, Pakistan. Mansour, known for his mercurial leadership, had been in the U.S. military's crosshairs for years.

See the forest, see the trees. Here lies the challenge in both performing and presenting an analysis. As data scientists, analysts, and machine learning engineers faced with fulfilling business objectives, we find ourselves bridging the gap between The Two Cultures: sciences and humanities. After spending countless hours at the terminal devising a creative and elegant solution to a difficult problem, the insights and business applications are obvious in our minds. But how do you distill them into something you can communicate? Presenting my work is one of the surprising challenges I faced in my recent transition from academia to life as a data analyst at a market research and strategy firm.

The simulator is an R package that streamlines the process of performing simulations by creating a common infrastructure that can be easily used and reused across projects. Methodological statisticians routinely write simulations to compare their methods to preexisting ones. While developing ideas, there is a temptation to write "quick and dirty" simulations to try out ideas. This approach of rapid prototyping is useful but can sometimes backfire if bugs are introduced. Using the simulator allows one to remove the "dirty" without sacrificing the "quick." Coding is quick because the statistician focuses exclusively on those aspects of the simulation that are specific to the particular paper being written. Code written with the simulator is succinct, highly readable, and easily shared with others. The modular nature of simulations written with the simulator promotes code reusability, which saves time and facilitates reproducibility. The syntax of the simulator leads to simulation code that is easily human-readable. Other benefits of using the simulator include the ability to "step in" to a simulation and change one aspect without having to rerun the entire simulation from scratch, the straightforward integration of parallel computing into simulations, and the ability to rapidly generate plots, tables, and reports with minimal effort.

In this study, we present and analyze a framework for geometric and topological estimation for mapping of unknown environments. We consider agents mimicking motion behaviors of cyborg insects, known as biobots, and exploit coordinate-free local interactions among them to infer geometric and topological information about the environment, under minimal sensing and localization constraints. Local interactions are used to create a graphical representation referred to as the encounter graph. A metric is estimated over the encounter graph of the agents in order to construct a geometric point cloud using manifold learning techniques. Topological data analysis (TDA), in particular persistent homology, is used in order to extract topological features of the space and a classification method is proposed to infer robust features of interest (e.g. existence of obstacles). We examine the asymptotic behavior of the proposed metric in terms of the convergence to the geodesic distances in the underlying manifold of the domain, and provide stability analysis results for the topological persistence. The proposed framework and its convergences and stability analysis are demonstrated through numerical simulations and experiments.