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To Teach Computers Math, Researchers Merge AI Approaches
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
“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
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
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
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?
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
Inspired by the results of a game-playing neural network, mathematicians have been making unexpected advances on an age-old math problem.
New Chip Expands the Possibilities for AI
An energy-efficient chip called NeuRRAM fixes an old design flaw to run large-scale AI algorithms on smaller devices, reaching the same accuracy as wasteful digital computers.
Machine Learning Highlights a Hidden Order in Scents
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.