We might be living in the least disruptive age in history This is a guest post by Brian Millar, Strategy Director at strategy agency Sense Worldwide. He works with global companies like Nike, Vodafone, and PepsiCo to transform their businesses. You can follow him on Twitter on @arthurascii "The world is moving faster than ever before. Everything is being disrupted, including that thing you do. Global Trends 2030: Alternative Worlds The National Intelligence Council has issued Global Trends 2030: Alternative Worlds, “intended to stimulate thinking about the rapid and vast geopolitical changes characterizing the world today and possible global trajectories during the next 15-20 years.” The report sees four megatrends: Individual empowerment will accelerate substantially during the next 15-20 years owing to poverty reduction and a huge growth of the global middle class, greater educational attainment, better health care, and widespread exploitation of new communications and manufacturing technologies. Enabled by communications technologies, power will shift toward multifaceted and amorphous networks that will form to influence state and global actions. Diffusion of power among countries will have a dramatic impact by 2030. Asia will have surpassed North America and Europe combined in terms of global power, based upon GDP, population size, military spending, and technological investment.
Causal Layered Analysis Defined Complexity requires us to examine futures-related issues from many angles and at multiple levels. Causal Layered Analysis (CLA) is a theory of knowledge and a methodology for creating more-effective policies and strategies. Since its invention in the late 1980s, it has been used successfully with governments, corporations, international think tanks, communities, and cities around the world. It has also been used as the primary research method for dozens of doctoral and master’s students around the world. CLA works at a number of levels, delving deeper than the litany, the headline, or a data level of reality to reach a systemic-level understanding of the causes for the litany.
Global Trends 2030: “Technological Center Of Gravity” To Shift To Asia By Juliana Chan | EditorialsDecember 14, 2012 A new report by the U.S. National Intelligence Council projects a shift in the ‘technological center of gravity’ to Asia by 2030. Imagining the Internet hy study the future? Because our existence depends upon the anticipation of what is to come and our preparation and policymaking responses. Writer H.G. Wells called for a "science of prediction" in 1902 in his "The Discovery of the Future." Since then, the study of the future has gradually become more formalized.
The American Indian And The "Great Emancipator" By Michael Gaddy Published 01. 9. 03 at 21:31 Sierra Time Perhaps the veneer of lies and historical distortions that surround Abraham Lincoln are beginning to crack. In the movie, "Gangs of New York," we finally have a historically correct representation of the real Abraham Lincoln and his policies. Heretofore, many socialistic intellectuals, politicians and historians have whitewashed these policies in order to protect Lincoln's image because of their allegiance to the unconstitutional centralization of power he brought to our government.
Use Data to Tell the Future: Understanding Machine Learning – Innovation Insi... When Amazon recommends a book you would like, Google predicts that you should leave now to get to your meeting on time, and Pandora magically creates your ideal playlist, these are examples of machine learning over a Big Data stream. With Big Data projected to drive enterprise IT spending to $242 Billion according to Gartner, Big Data is here to stay, and as a result, more businesses of every size are getting into the game. To many enterprise organizations Big Data represents a strategic asset -- it reflects the aggregate experience of the organization. The Class-Domination Theory of Power by G. William Domhoff NOTE: WhoRulesAmerica.net is largely based on my book, Who Rules America?, first published in 1967 and now in its 7th edition. This on-line document is presented as a summary of some of the main ideas in that book.
Shivon Zilis - Machine Intelligence Machine Intelligence in the Real World (this pieces was originally posted on Tech Crunch) . I’ve been laser-focused on machine intelligence in the past few years. I’ve talked to hundreds of entrepreneurs, researchers and investors about helping machines make us smarter. In the months since I shared my landscape of machine intelligence companies, folks keep asking me what I think of them — as if they’re all doing more or less the same thing.
What we read about deep learning is just the tip of the iceberg The artificial intelligence technique known as deep learning is white hot right now, as we have noted numerous times before. It’s powering many of the advances in computer vision, voice recognition and text analysis at companies including Google, Facebook, Microsoft and Baidu, and has been the technological foundation of many startups (some of which were acquired before even releasing a product). As far as machine learning goes, these public successes receive a lot of media attention. But they’re only the public face of a field that appears to be growing like mad beneath the surface. So much research is happening at places that are not large web companies, and even most of the large web companies’ work goes unreported.
Death of the Internet Despite these benefits, flooding the network with repeated messages has its own challenges. For transmitting data, the main questions are how data packet collisions “broadcast storms” are avoided, how the retransmitting process propagates the message efficiently toward its destination, and how the process ends, without an energy-wasting avalanche. Potentially a synchronised-Flooding approach using a synergic combination of techniques incorporating time division multiple access combined with high-accuracy synchronization would allow us to solve these challenges. Nodes transmit only relevant information, and retransmissions occur simultaneously so that the message propagates one hop in all directions at precisely the same time and avoids collisions, until the network reaches the set number of maximum hops and the message has flooded through the network.
The surprising thing robots can’t do yet: housework The race toward the Smart House of the future is barreling along, from Jibo the creepy home sidekick and Pepper the punny robot to near-military-grade vacuums. Yet between us and robotic domestic bliss, there remain some deceptively simple problems that take a large amount of computing. friction is very hard to account for. How machine learning will fuel huge innovation over the next 5 years Gaming execs:Join 180 select leaders from King, Glu, Rovio, Unity, Facebook, and more to plan your path to global domination in 2015. GamesBeat Summit is invite-only -- apply here. Ticket prices increase on March 6 Pacific!