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We are Big Idea Hunters…

We live in a time of information abundance, which far too many of us see as information overload. With the sum total of human knowledge, past and present, at our fingertips, we’re faced with a crisis of attention: which ideas should we engage with, and why? Big Think is an evolving roadmap to the best thinking on the planet — the ideas that can help you think flexibly and act decisively in a multivariate world.

A word about Big Ideas and Themes — The architecture of Big Think

Big ideas are lenses for envisioning the future. Every article and video on bigthink.com and on our learning platforms is based on an emerging “big idea” that is significant, widely relevant, and actionable. We’re sifting the noise for the questions and insights that have the power to change all of our lives, for decades to come. For example, reverse-engineering is a big idea in that the concept is increasingly useful across multiple disciplines, from education to nanotechnology.

Themes are the seven broad umbrellas under which we organize the hundreds of big ideas that populate Big Think. They include New World Order, Earth and Beyond, 21st Century Living, Going Mental, Extreme Biology, Power and Influence, and Inventing the Future.

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Robots Learn to Learn from Each Other, Not Just a Central Database

July 9, 2014, 3:00 PM

What's the Latest?

From self-parking cars to voice-recognition software on smartphones, the ability of individual machines to learn from collected sets of data is the forefront of artificial intelligence research. Now, a team of researchers from MIT have developed a new way for machines to learn directly from each other rather than taking in data from a central processing unit. "MIT's Laboratory for Information and Decision Systems have developed an algorithm in which distributed agents — such as robots exploring a building — collect data and analyze it independently. Pairs of agents, such as robots passing each other in the hall, then exchange analyses."

What's the Big Idea?

The new distributed algorithm outperformed the standard model which relies on a central processor of collected data. And while the model was mostly about robot collaboration, the results could affect big data as well, "since it would allow distributed servers to combine the results of their data analyses without aggregating the data at a central location." In the future, emergency response vehicles are expected to become increasingly automated so as to put fewer human lives at risk. In such a world, it would be essential for a team of land and air vehicles to accurately assess their surrounding environment and know how to respond as a coordinated team.

Read more at Kurzweil AI

Photo credit: Charles Taylor/Shutterstock


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