In the Statistics community, count data often receives special treatment (poisson, negative-binomial models etc.). Is there any special literature OR guidance available on using (Deep) Neural Networks for count-data?

This article was posted by Adrian Rosebrock on Pyimagesearch. Adrian is an entrepreneur and Ph.D who has launched two successful image search engines, ID My Pill and Chic Engine. This list is by no means exhaustive, it's simply a list of libraries that he has used in his computer vision career and found particular useful at one time or another. The goal of this blog post is to introduce you to these libraries. He encourages you to read up on each them individually to determine which one will work best for you in your particular situation.

Actor/director Seth Rogen let slip a few details about a new project this week. Appearing on Chris Hardwick's Nerdist podcast, Rogen revealed that he's currently writing a script that will be based on the singularity, a concept popularized by author and futurist Ray Kurzweil. The singularity, in a nutshell, is the time in human history in which artificial intelligence becomes so advanced that it allows humanity to enter the next stage of its evolution. While promoting his new film, Sausage Party, Rogen let slip the basics of the project. "It's called -- it's about singularity, it's about artificial intelligence," said Rogen.

This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers. To learn more and subscribe, please click here. Interest in the use of artificial intelligence in the workplace is continuing to heat up. This is exemplified by Interactions, a virtual assistant startup, which announced on Tuesday that it has secured 56 million during its most recent funding round, TechCrunch reports. The round was the largest to date, bringing the company's total funding to around 130 million.

For many people, the robot-populated future is a zero-sum game; it's either going to be us or them running things. Headlines -- and not just on conspiracy theory websites -- are rife with dire predictions like "Robots will take over most jobs in 30 years" and "The future has lots of robots, few jobs for humans." Lest one think they will be spared because they are in a "creative" or "people-oriented" discipline, this list should give even those folks something to worry about. "Computer art" -- where a computer uses algorithms to create a piece of art or music -- is an emerging technology. You know it's a serious endeavor when Google gets involved -- as the company did earlier this year with its new Magenta platform, which, according to the company, is "a research project to advance the state of the art in machine intelligence for music and art generation. Machine learning has already been used extensively to understand content, as in speech recognition or translation. With Magenta, we want to explore the other side -- developing algorithms that can learn how to generate art and music, potentially creating compelling and artistic content on their own."

Argyle Data, a leader in big data/machine learning analytics for mobile providers, has highlighted the role of supervised and unsupervised machine learning in detecting and preventing anomalous mobile traffic. The move comes as Argyle Data and Carnegie Mellon University (CMU) Silicon Valley's Department of Electrical and Computer Engineering prepare to publish a new research paper on anomaly detection, which will be presented at academic conferences during the first half of 2017. Global mobile fraud levels cost the industry an estimated U.S. 38 billion 2015 according to the latest CFCA survey. Most major attacks today are'fraud cocktails': unpredictable mixtures of several fraud types. The chief reason that operators are unable to detect complex new fraud is that approaches currently used to detect fraud in communications networks typically rely on static rules with pre-set thresholds, and can only detect known fraud types.

No, software will not render managers obsolete, but you will need to be more skilled than ever before. This article is part of an MIT SMR initiative exploring how technology is reshaping the practice of management. Editor's Note: This is the fifth in a special series of commissioned essays MIT Sloan Management Review will be publishing in Frontiers over the Spring and Summer of 2016. Each essay gives the author's response to this question: "Within the next five years, how will technology change the practice of management in a way we have not yet witnessed?" I've been thinking about technology and management for over a decade and in the process have written two books describing some of the ways the practice of management will respond to rapid technological innovations.

One approach to solving hard problems is to break them into computationally efficient parts. For instance, Globerson/Jaakkola do approximate counting by decomposing graph into planar graphs. In each part, the problem reduces to perfect matchings which can be solved efficiently on planar graph. Sontag/Jaakola solve subproblems on star-shaped subgraphs of original graph, the symmetry of star graph enabling a very fast solution to each subproblem. I recently came across graph class database which gives information on thousands of graph classes.

Technology is changing the way we live. Innovative products like smartwatches, virtual assistants like Siri and Cortana, and self-driving cars are raising the bar on expectations. So why shouldn't that change be reflected in the way we work? Business Insider spoke to Dave Wright, the chief strategy officer at cloud computing business ServiceNow about what they're doing to improve processes and productivity and the workplace, as well as trends we're likely to see in the future. But first if you're not sure what ServiceNow does, here's how Wright explains it.

Neuroscience innovation is colliding with digital technology in unprecedented ways. Advances in machine learning, AI, and Virtual/Augmented Reality are revolutionizing brain health and wellness. Our diverse panel includes experts in Neurosurgery, Psychiatry, Digital Health, and VR/AR. We will illustrate the latest uses of neurotechnology for targeted treatment of brain and behavioral health disorders. These will include examples from mental health, VR/AR, neuro-gaming, wearables, brain surgery, and medical devices.