With online viewership and sales growing rapidly, enterprises are interested in understanding how they analyze performance to positively impact business metrics. Deeper insight into the user experience is needed to understand why conversions are dropping and/or bounce rates are increasing or, preferably, to understand what has been helping these metrics improve. The digital performance management industry has evolved as application performance management companies have broadened their scope beyond synthetic testing that simulates users loading specific pages at regular intervals to include web and mobile testing, and real user monitoring (RUM). As synthetic monitoring gained popularity, performance engineers realized the variations that exist from real end users were not being captured. This led to the introduction of RUM - the process of capturing, analyzing and reporting data from a real end user's interaction with a website.

Artificial Intelligence Poised to Double Annual Economic Growth Rate in 12 Developed Economies and Boost Labor Productivity by up to 40 Percent by 2035, According to New Research by Accenture NEW YORK; Sept. 28, 2016 – Research released today from Accenture (NYSE: ACN) reveals that artificial intelligence (AI) could double annual economic growth rates by 2035 by changing the nature of work and spawning a new relationship between man and machine. The impact of AI technologies on business is projected to boost labor productivity by up to 40 percent by fundamentally changing the way work is done and reinforcing the role of people to drive growth in business. "AI is poised to transform business in ways we've not seen since the impact of computer technology in the late 20th century," said Paul Daugherty, chief technology officer, Accenture. "The combinatorial effect of AI, cloud, sophisticated analytics and other technologies is already starting to change how work is done by humans and computers, and how organizations interact with consumers in startling ways. Our research demonstrates that as AI matures, it can propel economic growth and potentially serve as a powerful remedy for stagnant productivity and labor shortages of recent decades."

When the U.S. globalization push of the 1990s outsourced manufacturing, proponents could not have known the full impact this shift would have at home. Not only were many towns wiped out, their commerce to be replaced by service industries, but the manufacturing sector itself would struggle with the loss of infrastructure -- buildings and machinery -- and with manufacturing intelligence as well. Manufacturing intelligence, the kind of know-how and workers that we need to take back industries, was lost. The country's shrinking manufacturing base benefited many other global economies, however. China, of course, became a major trade partner.

As the automated, intelligent conversation settles into its role as a major marketing channel, a variety of chatbot authoring platforms have made their entrance. This week, a new one promises to be "the most complete conversational computing platform available." The PullString Platform, based on technology previously employed for Call of Duty's Lt. Reyes chatbot on Facebook Messenger and Mattel's Hello Barbie doll, is now open to the public after five years of development. The company, formerly called ToyTalk, was founded in 2011. About a quarter of the 40-person staff for the San Francisco-based company came from the animation studio Pixar, and the intent is to provide a platform that goes beyond chatbots.

It's unavoidable: the Internet of Things will kill many jobs. Self-driving cars alone could put millions out of work. And the manufacturing sector, already reeling from decades of job losses, could see millions of more jobs replaced by machines. The convergence of IoT and cognitive computing could also threaten many prestigious jobs as computers learn to perform thinking tasks rather than solely mechanical ones. "We will soon be looking at hordes of citizens of zero economic value," write venture investor William H. Davidow and technology writer Michael S. Malone in Harvard Business Review. "Figuring out how to deal with the impacts of this development will be the greatest challenge facing free market economies in this century."

Artificial Intelligence has been the holy grail of Computer Science for over a hundred years and we are finally starting to scratch the first layer of this incredibly complex system. Currently, all the major players in the Technology business are investing heavily in the R&D of AI systems, but it would seem we are still very far away from the development of a true AI. To truly get a good grasp on where the industry stood in its quest for intelligent machines, we sat down with John Giannandrea, the former Head of Machine Learning and currently the SVP Search at Google, for a one-on-one. From the conversation, it became clear that we have had the latest developments in automation all wrong, and here is the real picture. John was quick to clarify that there are three distinct levels of Machine Intelligence; Machine Learning, Machine Intelligence and Artificial Intelligence.

The first comic that cartoonist Gene Luen Yang ever bought was a two-in-one issue that featured a man made out of rocks and an intergalactic cyborg. He loved comics, especially the kind that featured space aliens. So he started making his own. He and a friend drew comics and sold them for 50 cents each. Among their earliest creations were the "Trans-Smurfers," Smurfs who transformed into robotic fruit. They also flew and fought crime.

The Senior Computer Vision Expert will also very closely work with Subject Matter Experts and Business Analysts to rapidly understand a specific business domain and iteratively refine the analyses and the learning models to create high-fidelity automated analytics solutions.

Summary: This is my favorite IoT story. We are so used to IoT platforms being physical objects that we forget about the potential for biologics. In terms of direct economic reward little will compare to this story about the IoT and cows. This is my favorite IoT story which I first heard from Joseph Sirosh, CVP of Machine Learning for Microsoft at the spring Strata convention in San Jose. We are so used to IoT platforms being physical objects like cars or thermostats or gaming consoles that we forget about the potential for biologics.

Prof Raghavan also serves as the Director of the NSF-sponsored Industry/ University Cooperative Research Center for Visual and Decision Informatics. In this role, he co-ordinates several multi-institutional, industry-driven research projects and manages a budget of over 500K/year. From 1997 to 2003, he led a 2.3M research and development project in close collaboration with the USGS National Wetlands Research Center and with the Department of Energy's Office of Science and Technical Information on creating a digital library with data mining capabilities incorporated. His research interests are in Big Data, data mining, information retrieval, machine learning and Internet computing. He has published over 250 peer-reviewed research papers --appearing in top-level journals and proceedings - that cumulatively accord him an h-index of 31, based on citations.