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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.
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.
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.