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Language processing programs are notoriously hard to interpret, but smaller versions can provide important insights into how they work.

The existence of secure cryptography depends on one of the oldest questions in computational complexity.

Traditional algorithms power complicated computational tools like machine learning. A new approach, called algorithms with predictions, uses the power of machine learning to improve algorithms.

A simple algorithm that revolutionizes how neural networks approach language is now taking on image classification as well. It may not stop there.

For the first time, experiments demonstrate the possibility of sharing secrets with perfect privacy — even when the devices used to share them cannot be trusted.

Algorithms that use the brain’s communication signal can now work on analog neuromorphic chips, which closely mimic our energy-efficient brains.

Two recent collaborations between mathematicians and DeepMind demonstrate the potential of machine learning to help researchers generate new mathematical conjectures.

Two researchers show that for neural networks to be able to remember better, they need far more parameters than previously thought.

Two teams have shown how quantum approaches can solve problems faster than classical computers, bringing physics and computer science closer together.