Learning by omission

What would happen if neural networks were explicitly trained to discard useless information, and how to tell them to do so, is the subject of recent research by SFI's Artemy Kolchinsky, Brendan Tracey, and David Wolpert.

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What magnets have to do with pistachios

SFI External Professor Jon Machta and colleagues from the University of California, Davis, show that one of the most famous models in statistical physics, the Ising model, could be used to understand why pistachio trees bloom in synchrony.

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In memoriam: Alfred Hübler

A teacher, physicist, and all-around “high throughput” individual, SFI External Professor Alfred Hübler passed away Saturday, January 27, at the age of 60.

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How living systems compute solutions to problems

No individual fish or bee or neuron has enough information by itself to solve a complex problem, but together they can accomplish amazing things. In research recently published in Science Advances, Eleanor Brush (University of Maryland), David Krakauer, and Jessica Flack address how this is possible through a study of the emergence of social structure in primate social groups.

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Let us compute: The law

The first working group in Feldstein Program on Law, History, and Regulation brings leading researchers together to contribute to the burgeoning research field in the computational study of law.

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What are the limits of scientific understanding?

Exploring the limits of scientific understanding is the query that will drive a three-day workshop at SFI, which itself aims to understand how well scientific and mathematical reasoning can comprehend complex systems.

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