Cooler computing through statistical physics?

Recent breakthroughs in the field of nonequilibrium statistical physics have revealed opportunities to advance the “thermodynamics of computation," a branch of computer science that could have far-reaching consequences for how we understand, and engineer, our computers.

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Learn agent-based modeling with Bill Rand

Agent-based modeling has been used to study everything from economics to biology to political science to business and management. This July, programmers and non-programmers alike can learn to model by enrolling in Introduction to Agent-based Modeling, Complexity Explorer’s massive open online course (MOOC).

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SFI Press publishes Emergence of Premodern States

On June 11, the SFI Press released the second volume in its Seminar Series, The Emergence of Premodern States, edited by Jeremy A. Sabloff and Paula L.W. Sabloff. This project tackles one of the most deceptively simple inquiries in archaeology: How did humans transition from hunter-gatherer societies into states — collective entities that are the movers and shakers of the modern world?

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An Introduction to SFI’s Visiting Faculty

Three researchers are spending several months at SFI to tackle some big questions: “Why do we sleep less as we get older?” “What do city pigeons have in common with drug interactions?” and “Is there a trajectory underlying human history?” to name a few.

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New study improves 'crowd wisdom' estimates

In a new study, researchers examined just how accurate our collective intelligence is and how individual bias and information sharing skew aggregate estimates. Using their findings, they developed a mathematical correction that takes into account bias and social information to generate an improved crowd estimate. 

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Machine learning yields new insights into French Revolution’s early days

New research from an interdisciplinary collaboration among historians, political scientists, and statisticians suggests that rhetorical innovations may have played a significant role in winning acceptance for the new principles of governance that built the French republic’s foundation — and inspired future democracies around the world. 

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Finding meaning in big data

The noise in high-dimensional datasets can obscure real correlations — and give rise to illusory patterns that don’t mean anything. April 2-5, an interdisciplinary group of mathematicians, physicists, and theoretical computer scientists meets at SFI to address the problem and devise new algorithms that can succeed all the way up to the limits that arise from not having enough data, or not knowing if the data is accurate.  

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