Computer Science

Efforts to build a better digital “nose” suggest that our perception of scents reflects both the structure of aromatic molecules and the metabolic processes that make them.

A custom-built machine learning algorithm can predict when a complex system is about to switch to a wildly different mode of behavior.

Neural networks originally designed for language processing turn out to be great models of how our brains understand places.

What’s a message, really? Claude Shannon recognized that the elemental ingredient is surprise.

Anima Anandkumar wants computer scientists to move beyond the matrix, among other challenges.

Two researchers have broken an encryption protocol that many saw as a promising defense against the power of quantum computing.

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful.

Christopher Kanan is building algorithms that can continuously learn over time — the way we do.

Three computer scientists have posted a proof of the NLTS conjecture, showing that systems of entangled particles can remain difficult to analyze even away from extremes.