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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.
Chaos Researchers Can Now Predict Perilous Points of No Return
A custom-built machine learning algorithm can predict when a complex system is about to switch to a wildly different mode of behavior.
How Transformers Seem to Mimic Parts of the Brain
Neural networks originally designed for language processing turn out to be great models of how our brains understand places.
The AI Researcher Giving Her Field Its Bitter Medicine
Anima Anandkumar wants computer scientists to move beyond the matrix, among other challenges.
Self-Taught AI Shows Similarities to How the Brain Works
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.
The Computer Scientist Challenging AI to Learn Better
Christopher Kanan is building algorithms that can continuously learn over time — the way we do.
Can Computers Be Mathematicians?
Artificial intelligence has bested humans at problem-solving challenges like chess and Go. Is mathematics research next? Steven Strogatz speaks with mathematician Kevin Buzzard to learn about the effort to translate math into language that computers understand.