The “Sharing Economy,” the “economy of the commons,” deserves and needs a point of reference equivalent to the large institutions of European social theory.
THE MOMENTOUS LEAP Spiral Dynamics in Action: Deciphering the Master Code in the Age of Complexity, Collaboration and Emergence. A Functional, Integral Pathway
to a Sustainable Future
This is where the issue of Phil Schneider comes in. He is a UFO whistleblower who spent his short life saying what was, when he said it, seemed outlandish. We are now putting so many of his 30 year old technologies into use, so many are now public or at least to the advanced defense community that more and more of us accept all of it.
Automating filtering via machine learning is an up-and-coming research category for infotention — Howard ” “Predicting items a user would like on the basis of other users’ ratings for these items has become a well-established strategy adopted by many recommendation services on the Internet. Although this can be seen as a classification problem, algorithms proposed thus far do not draw on results from the machine learning literature. We propose a representation for collaborative filtering tasks that allows the application of virtually any machine learning algorithm. We identify the shortcomings of current collaborative filtering techniques and propose the use of learning algorithms paired with feature extraction techniques that specifically address the limitations of previous approaches.”
The Zoetrope is a vertical-axis wind turbine made from common materials such as stove pipe, metal brackets, plastic sheet and a trailer hub. Many of the materials can be found at local hardware or home improvement stores, the rest can either be made at home or purchased online.
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Applied Sciences made the decision to open source the wind turbine and provide a freely available introduction to wind power, thereby allowing others to improve the design and functionality. The construction guide represents a realization of the open source decision. It details the build process and includes a complete materials list as well as recommended tools.
My colleague Robert Kirkpatrick from Global Pulse has been actively promoting the concept of “data philanthropy” within the context of development. Data philanthropy involves companies sharing proprietary datasets for social good. I believe we urgently need big (social) data philanthropy for humanitarian response as well. Disaster-affected communities are increasingly the source of big data, which they generate and share via social media platforms like twitter. Processing this data manually, however, is very time consuming and resource intensive. Indeed, large numbers of digital humanitarian volunteers are often needed to monitor and process user-generated content from disaster-affected communities in near real-time.
Meanwhile, companies like Crimson Hexagon, Geofeedia, NetBase, Netvibes, RecordedFuture and Social Flow are defining the cutting edge of automated methods for media monitoring and analysis. So why not set up a Big Data Philanthropy group for humanitarian response in partnership with the Digital Humanitarian Network? Call it Corporate Social Responsibility (CRS) for digital humanitarian response. These companies would benefit from the publicity of supporting such positive and highly visible efforts. They would also receive expert feedback on their tools.