Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

In 2017, Roger Guimerà and Marta Sales-Pardo discovered a cause of cell division, the process driving the growth of living beings. But they couldn’t immediately reveal how they learned the answer. The ...

Technological devices are getting ever smaller, but as they approach the scale at which quantum physics matters, our understanding of how they interact with their environment evaporates. James Millen ...

Xaba’s AI-powered software solutions enables robots to self-generate programming of Robots and CNC machinery. The company hopes to remediate machining methods typically relegated to more expensive and ...

image of Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Credit: ...

A case study in aerospace manufacturing provides an overview of how physics-informed digital twin systems transform robotics processes—from adaptive process planning and real-time process monitoring ...

Don’t know your convolutional neural networks from your boosted decision trees? Symmetry is here to help. It’s time for some deep learning. Check out this list to pick up some new terminology—and ...