Teaching physics to neural networks removes 'chaos blindness'

Researchers from North Carolina State University have discovered that teaching physics to neural networks enables those networks to better adapt to chaos within their environment. The work has implications for improved artificial ...

Machine learning unlocks mysteries of quantum physics

Understanding electrons' intricate behavior has led to discoveries that transformed society, such as the revolution in computing made possible by the invention of the transistor.

The future of artificial intelligence

Only a few years ago, it would have seemed improbable to assume that a piece of technology could quickly and accurately understand most of what you say – let alone translate it into another language.

New AI algorithm taught by humans learns beyond its training

"Hey Siri, how's my hair?" Your smartphone may soon be able to give you an honest answer, thanks to a new machine learning algorithm designed by U of T Engineering researchers Parham Aarabi and Wenzhi Guo.

Introducing quantum convolutional neural networks

Machine learning techniques have so far proved to be very promising for the analysis of data in several fields, with many potential applications. However, researchers have found that applying these methods to quantum physics ...

The thermodynamics of learning

(Phys.org)—While investigating how efficiently the brain can learn new information, physicists have found that, at the neuronal level, learning efficiency is ultimately limited by the laws of thermodynamics—the same principles ...

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