A group of scientists may have stumbled upon a radical new way to do cosmology. Cosmologists usually determine the composition of the universe by observing as much of it as possible. But these researchers have found that a machine learning algorithm can scrutinize a single simulated galaxy and predict the overall makeup of the digital universe in which it exists--a feat analogous to analyzing a random grain of sand under a microscope and working out the mass of Eurasia. The machines appear to have found a pattern that might someday allow astronomers to draw sweeping conclusions about the real cosmos merely by studying its elemental building blocks. Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

Some believe it will present us with innovative solutions to a myriad of problems, others believe it will signal the demise of all mankind. In an effort to learn more about the current state of this exciting technology, and cut through the noise, I jumped at the opportunity to listen and learn from Galina Alperovich, senior machine learning researcher at Avast, during the Digital Transformation EXPO Europe, currently in its 15th year of congregating the most influential innovators and practitioners from around the globe. Avast uses a network comprised of hundreds of millions of sensors (their end-users) that funnel data into the company's A.I. system, in order to detect and defend against cyber threats. "For cybersecurity, A.I. is super important," according to Ondrej Vlcek, chief executive officer of Avast. "A.I. is a great tool for cybersecurity to provide better defense and protection against attacks."[1]

George Dyson was born in 1953 and had a unique opportunity to witness firsthand the conjunction of mathematics and physics that brought the digital revolution to life. He has been observing the relationship between nature and technology ever since. Dyson's latest book, Turing's Cathedral: The Origins of the Digital Universe, illuminates the transition from numbers that mean things to numbers that do things in the aftermath of World War II. I am very happy I had the opportunity to have him appear on Singularity 1 on 1 where we talked for over an hour. During our discussion with Dyson we cover a very wide variety of topics such as: his unique childhood of growing up as the son of theoretical physicist Freeman Dyson; playing around the Institute for Advanced Studies in Princeton; having Helen Dukas i.e. Einstein's secretary as a babysitter; his interest in boats and boat-building as inspired by reading Kon-Tiki; George's previous book titled Darwin Among The Machines; Samuel Butler and Ted Kaczynski; Turing's Cathedral and the origins of our digital universe; Alan Turing and John von Neumann; the hydrogen bomb and what von Neumann called "the deal with the devil"; technology's power to liberate and/or enslave; artificial intelligence, the technological singularity and our chances of surviving it.

While financial institutions are still in the early stages of adopting AI technologies, intelligent machines are expected to become the most defining for the future of institutions in the financial services and insurance industries. In fact, estimates suggest that 75% of insurance executives believe that AI will either significantly alter or completely transform the insurance industry by 2020. Moreover, one-third believe that their own company will be completely transformed by AI within that timeframe. AI is expected to redefine the way financial institutions gain information from and interact with their customers, with the benefits of embedding AI into user interfaces being better data analysis and insight. A range of institutions are already either experimenting or have implemented AI/ML capabilities into various processes, with benefits encompassing improvement of straight-through reconciliation (STR) of incoming payments, higher conversions from service recommendation engine, better understanding of customer behavior and preferences, large-scale automation, etc.

While financial institutions are still in the early stages of adopting AI technologies, intelligent machines are expected to become the most defining tech for the future of institutions in the financial services and insurance industries. In fact, estimates suggest that 75% of insurance executives believe that AI will either significantly alter or completely transform the insurance industry by 2020. Moreover, one-third believe that their own company will be completely transformed by AI within that timeframe. AI is expected to redefine the way financial institutions gain information from and interact with their customers, with the benefits of embedding AI into user interfaces being better data analysis and insight. A range of institutions are already either experimenting or have implemented AI/ML capabilities into various processes, with benefits encompassing improvement of straight-through reconciliation (STR) of incoming payments, higher conversions from service recommendation engine, better understanding of customer behavior and preferences, large-scale automation, etc.

"Over the last decade, machine learning, which is part of artificial intelligence (AI), has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome." Movements can be recognised, memorised, interpreted and shared through networks. There are many applications in health, sports and especially education in the digital age. "Driven by advances in artificial intelligence and natural language processing, voice is slowly establishing itself as the new interface to reach the digital universe." Gestures are thus another emerging interface to reach the digital universe.

"Over the last decade, machine learning, which is part of artificial intelligence (AI), has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome." Movements can be recognised, memorised, interpreted and shared through networks. There are many applications in health, sports and especially education in the digital age. "Driven by advances in artificial intelligence and natural language processing, voice is slowly establishing itself as the new interface to reach the digital universe." Gestures are thus another emerging interface to reach the digital universe.

Regardless of the media's incessant worship of the new "Zucks", and the President's desire for "every kid to code", there is something to be said for an individual that views themselves and their efforts as a part of the bigger picture. Striving for knowledge brought me beyond the horizons of discernible. Herzlichen Dank! to my publisher BIZCATALYST 360, so big-heartedly edited by Mr. Dennis J. Pitocco, who, I believe is turning undiscovered talents into international success stories. And by that I mean people who want to read … Herzlichen Dank und viele Grüße to all my readers worldwide! The word'unprecedented' seems too weak to convey just how much the dimensionless operational space of digital (r)evolution requires instantaneous reaction.

Hewlett Packard Enterprise (HPE) Co has unveiled a new computer prototype that it claims could handle more data than any similar system in the world. The California-based firm said the prototype contains 160 terabytes of memory, capable of managing the information from every book in the U.S. Library of Congress five times over. It is the latest prototype from'The Machine' research project by HPE, which aims to create super-fast computers by designing them around memory. Photonics/Optical communication links, including the new X1 photonics module, are online and operational. Software programming tools designed to take advantage of abundant persistent memory.

Across enterprises, ever-expanding stores of data remain unstructured and unanalyzed. Few organizations have been able to explore nontraditional data sources such as image, audio, and video files; the torrent of machine and sensor information generated by the Internet of Things; and the enormous troves of raw data found in the unexplored recesses of the "deep web." However, recent advances in computer vision, pattern recognition, and cognitive analytics are making it possible for companies to shine a light on these untapped sources and derive insights that lead to better experiences and decision making across the business. In this age of technology-driven enlightenment, data is our competitive currency. Buried within raw information generated in mind-boggling volumes by transactional systems, social media, search engines, and countless other technologies are critical strategic, customer, and operational insights that, once illuminated by analytics, can validate or clarify assumptions, inform decision making, and help chart new paths to the future. Until recently, taking a passive, backward-looking approach to data and analytics was standard practice. With the ultimate goal of "generating a report," organizations frequently applied analytics capabilities to limited samples of structured data siloed within a specific system or company function. Moreover, nagging quality issues with master data, lack of user sophistication, and the inability to bring together data from across enterprise systems often colluded to produce insights that were at best limited in scope and, at worst, misleading.