Deep learning — which uses multilayered neural networks to elicit patterns from data — was getting really hot back then. There was already a lot of excitement about applications in image ...

Luzhe Huang, Hanlong Chen, Tairan Liu, Aydogan Ozcan. Self-supervised learning of hologram reconstruction using physics consistency. Nature Machine Intelligence, 2023; DOI: 10.1038/s42256-023-00704-7 ...

When did you first try to combine physics with deep learning? Rose Yu: It started with traffic. I was a grad student at USC, and the campus is right near the intersection of I-10 and I-110. To get ...

The prize goes to John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks,” the Royal Swedish Academy of ...

The 2024 Nobel Prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their fundamental discoveries in machine learning, which paved the way for how artificial intelligence is ...

robot parade New physics sim trains robots 430,000 times faster than reality "Genesis" can compress training times from decades into hours using 3D worlds conjured from text.