Category Physics

Researchers look to machine learning to optimize the design and control of stellarators and tokamaks. Researchers are using artificial intelligence to perfect the design of the vessels surrounding the super-hot plasma, optimize heating methods and maintain stable control of the reaction for increasingly long periods. A new article explains how a researcher team used machine learning to avoid magnetic perturbations, or disruptions, which destabilize fusion plasma.

The intricate dance of atoms fusing and releasing energy has fascinated scientists for decades. Now, human ingenuity and artificial intelligence are coming together at the U.S...

MIT physicists and colleagues have created a five-lane superhighway for electrons that could allow ultra-efficient electronics and more. The work, reported in the May 9 issue of Science, is one of several important discoveries by the same team over the last year involving a material that is essentially a unique form of pencil lead.

“This discovery has direct implications for low-power electronic devices because no energy is lost during the propagation of electrons, which is not the case in regular materials where the electrons are scattered,” says Long Ju, an assistant professor in the ...

Many artificial intelligence (AI) systems have already learned how to deceive humans, even systems that have been trained to be helpful and honest. In a review article published in the journal Patterns on May 10, researchers describe the risks of deception by AI systems and call for governments to develop strong regulations to address this issue as soon as possible.

“AI developers do not have a confident understanding of what causes undesirable AI behaviors like deception,” says first author Peter S. Park, an AI existential safety postdoctoral fellow at MIT. “But generally speaking, we think AI deception arises because a deception-based strategy turned out to be the best way to perform well at the given AI’s training task. Deception helps them achieve their goals.”

Park and coll...

Cornell researchers have developed a robotic feeding system that uses computer vision, machine learning and multimodal sensing to safely feed people with severe mobility limitations, including those with spinal cord injuries, cerebralpalsy and multiple sclerosis.

“Feeding individuals with severe mobility limitations with a robot is difficult, as many cannot lean forward and require food to be placed directly inside their mouths,” said Tapomayukh “Tapo” Bhattacharjee, assistant professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science and senior developer behind the system...