A video summary of the paper: Nguyen A, Yosinski J, Clune J. Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images. The paper is available here: http://EvolvingAI.org/fooling Special thanks to those who created the music, images, videos and software that were used to create this video.

ROOBO, a fast-growing hardware and AI startup headquartered in Beijing, today unveiled a prototype of its newest product, a "pet robot" called Domgy. For the unfamiliar, ROOBO is the company behind Pudding, a voice-controlled, educational robot for kids. Pudding is used to teach kids vocabulary, geography, jokes and more. The company also makes the Idealens virtual reality headset, Skyseries drone and Runbone earbuds. Since its founding in 2014, ROOBO has grown to 300 employees, with 7 worldwide offices, including one in Seattle.

Microsoft (NASDAQ:MSFT) co-founder Bill Gates recently called artificial intelligence "the holy grail that anyone in computer science has been thinking about" during Vox Media's Code Conference. Gates discussed the rapid progress of speech recognition and computer vision technologies over the past five years, and noted that "the dream is finally arriving." If that dream arrives, tech investors should recognize the major trends and players in this market. To get started, let's examine 10 fascinating facts about the AI industry. Research firm Markets and Markets estimates that the AI market will grow from 420 million in 2014 to 5.05 billion by 2020, thanks to the rising adoption of machine learning and natural language processing technologies in the media, advertising, retail, finance, and healthcare industries.

Facebook is getting even closer to a human-level understanding of what people are saying. Facebook has developed DeepText, a new way to parse text using artificial intelligence processes that's quicker at picking up new languages and slang than traditional approaches. In a company blog post published on Wednesday, three members of the company's applied machine learning team -- Ahmad Abdulkader, Aparna Lakshmiratan and Joy Zhang -- announced the technology that's already being used across Facebook and Facebook Messenger. DeepText is able to churn through "several thousands of posts per second" across more than 20 languages and understand what's being communicated with "near-human accuracy," according to the announcement post. Facebook's ability to comprehend what people are saying on its platform isn't new.

Marketing today is a labour intensive task. It requires marketers to dig through large volumes of data – most of which doesn't really help them make impactful business decisions in the long run. According to EMC, the digital universe is all set to grow by a factor of 300, from 130 exabytes to 40,000 exabytes by 2020. But the truth is that the human kind can only retain upto 1m gigabytes of memory. While there are those who believe'data is everything', the truth is that what you learn from the data and what you do with it, is what actually matters.

Mar 11, 2016 AlphaGo, a computer program developed by Google DeepMind in London to play the traditional Chinese board game Go, had five matches against Se-Dol Lee, a professional Go player in Korea from March 8-15, 2016. AlphaGo won four out of the five games, a significant test result showcasing the advancement achieved in the field of general-purpose artificial intelligence (GAI), according to the company. Dr. Demis Hassabis, the Chief Executive Officer of Google DeepMind, visited KAIST on March 11, 2016 and gave an hour-long talk to students and faculty. In the lecture, which was entitled "Artificial Intelligence and the Future," he introduced an overview of GAI and some of its applications in Atari video games and Go.

I've looked previously at the rise of so-called automated leadership, with the scheduling and appraisal of employees largely done via algorithm, with researchers exploring just how people feel working under this kind of leadership. That is but one part of the infusion of automation into leadership, however, with things like forecasting and other forms of data analysis handed over to computers for a while now. A team from the University of York and software company MooD International are teaming up to use a mixture of AI and gaming technology to help management decision making. The work revolves around the so-called Monte Carlo Tree Search, which is a commonly used algorithm for decision-making in video games. The aim is to make a similar algorithm for use in the workplace.

These and many other insights are from the Evans Data Corporation Global Development Survey, Volume 1 (PDF, client access) published earlier this month. The methodology was based on interviews with developers actively creating new applications with the latest technologies. The Evans Data Corporation (EDC),International Panel of Developers, were sent invitations to participate and complete the survey online. Please see page 17 of the study for additional details on the methodology.

By regression, I mean the derivation of a continuous property of an image (e.g. the mean area of the objects shown on the image) from its pixeldata. I'd like to train the algorithm with several images with known properties, in order to use it to analyze unknown images. From my limited understanding, this should be possible. Nevertheless, I only found examples of image classification or regressions of numerical values. Therefore, I'd be very thankful for hints to examples or tutorials.

Although numeric data is easy to work with in Python, most knowledge created by humans is actually raw, unstructured text. By learning how to transform text into data that is usable by machine learning models, you drastically increase the amount of data that your models can learn from. In this tutorial, we'll build and evaluate predictive models from real-world text using scikit-learn. Subscribe to the Data School newsletter: http://www.dataschool.io/subscribe/ OTHER RESOURCES My scikit-learn video series: https://www.youtube.com/playlist?list... My pandas video series: https://www.youtube.com/playlist?list... JOIN THE DATA SCHOOL COMMUNITY Blog: http://www.dataschool.io