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In Neural Networks, Unbreakable Locks Can Hide Invisible Doors

March 2, 2023

Cryptographers have shown how perfect security can undermine machine learning models.

Q&A

An Applied Mathematician With an Unexpected Toolbox

March 1, 2023

Lek-Heng Lim uses tools from algebra, geometry and topology to answer questions in machine learning.

To Teach Computers Math, Researchers Merge AI Approaches

February 15, 2023

Large language models still struggle with basic reasoning tasks. Two new papers that apply machine learning to math provide a blueprint for how that could change.

Researchers Discover a More Flexible Approach to Machine Learning

February 7, 2023

“Liquid” neural nets, based on a worm’s nervous system, can transform their underlying algorithms on the fly, giving them unprecedented speed and adaptability.

Machines Learn Better if We Teach Them the Basics

February 1, 2023

A wave of research improves reinforcement learning algorithms by pre-training them as if they were human.

The Physics Principle That Inspired Modern AI Art

January 5, 2023

Diffusion models generate incredible images by learning to reverse the process that, among other things, causes ink to spread through water.

The Year in Computer Science

December 21, 2022

Computer scientists this year learned how to transmit perfect secrets, why transformers seem so good at everything, and how to improve on decades-old algorithms (with a little help from AI).

What Does It Mean to Align AI With Human Values?

December 13, 2022

Making sure our machines understand the intent behind our instructions is an important problem that requires understanding intelligence itself.

AI Reveals New Possibilities in Matrix Multiplication

November 23, 2022

Inspired by the results of a game-playing neural network, mathematicians have been making unexpected advances on an age-old math problem.

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