(Roughly) Daily

“Man is not born to solve the problem of the universe, but to find out what he has to do; and to restrain himself within the limits of his comprehension”*…

 

Half a century ago, the pioneers of chaos theory discovered that the “butterfly effect” makes long-term prediction impossible. Even the smallest perturbation to a complex system (like the weather, the economy or just about anything else) can touch off a concatenation of events that leads to a dramatically divergent future. Unable to pin down the state of these systems precisely enough to predict how they’ll play out, we live under a veil of uncertainty.

But now the robots are here to help…

In new computer experiments, artificial-intelligence algorithms can tell the future of chaotic systems.  For example, researchers have used machine learning to predict the chaotic evolution of a model flame front like the one pictured above.  Learn how– and what it may mean– at “Machine Learning’s ‘Amazing’ Ability to Predict Chaos.”

* Johann Wolfgang von Goethe

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As we contemplate complexity, we might might recall that it was on this date in 1961 that Robert Noyce was issued patent number 2981877 for his “semiconductor device-and-lead structure,” the first patent for what would come to be known as the integrated circuit.  In fact another engineer, Jack Kilby, had separately and essentially simultaneously developed the same technology (Kilby’s design was rooted in germanium; Noyce’s in silicon) and has filed a few months earlier than Noyce… a fact that was recognized in 2000 when Kilby was Awarded the Nobel Prize– in which Noyce, who had died in 1990, did not share.

Noyce (left) and Kilby (right)

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