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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.
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.
By Exploring Virtual Worlds, AI Learns in New Ways
Intelligent beings learn by interacting with the world. Artificial intelligence researchers have adopted a similar strategy to teach their virtual agents new tricks.
Will Transformers Take Over Artificial Intelligence?
A simple algorithm that revolutionizes how neural networks approach language is now taking on image classification as well. It may not stop there.
AI Overcomes Stumbling Block on Brain-Inspired Hardware
Algorithms that use the brain’s communication signal can now work on analog neuromorphic chips, which closely mimic our energy-efficient brains.