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The Physical Process That Powers a New Type of Generative AI
Some modern image generators rely on the principles of diffusion to create images. Alternatives based on the process behind the distribution of charged particles may yield even better results.
Machine Learning Aids Classical Modeling of Quantum Systems
By using “classical shadows,” ordinary computers can beat quantum computers at the tricky task of understanding quantum behaviors.
Why Mathematical Proof Is a Social Compact
Number theorist Andrew Granville on what mathematics really is — and why objectivity is never quite within reach.
The AI Tools Making Images Look Better
Researchers have discovered ways around a fundamental trade-off between accuracy and beauty in digital images.
Risky Giant Steps Can Solve Optimization Problems Faster
New results break with decades of conventional wisdom for the gradient descent algorithm.
Neural Networks Need Data to Learn. Even If It’s Fake.
Real data can be hard to get, so researchers are turning to synthetic data to train their artificial intelligence systems.
Sparse Networks Come to the Aid of Big Physics
A novel type of neural network is helping physicists with the daunting challenge of data analysis.
Some Neural Networks Learn Language Like Humans
Researchers uncover striking parallels in the ways that humans and machine learning models acquire language skills.
Secret Messages Can Hide in AI-Generated Media
In steganography, an ordinary message masks the presence of a secret communication. Humans can never do it perfectly, but a new study shows it’s possible for machines.