Energy & Green Tech
Research at the Vitoria-Gasteiz Faculty of Engineering of the UPV/EHU has used convolutional neural networks to predict airflow characteristics in the aerodynamic profiles of high-power wind turbines, and has shown that flow ...
Aug 8, 2022
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60
Engineering
Researchers from Santa Clara University, New Jersey Institute of Technology and the University of Hong Kong have been able to successfully teach microrobots how to swim via deep reinforcement learning, marking a substantial ...
Aug 5, 2022
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208
Computer Sciences
Researchers at the University of Missouri are applying a form of artificial intelligence (AI)—previously used to analyze how National Basketball Association (NBA) players move their bodies—to now help scientists develop ...
May 5, 2022
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183
Robotics
To be truly useful, drones—that is, autonomous flying vehicles—will need to learn to navigate real-world weather and wind conditions.
May 4, 2022
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155
Automotive
Almost 75 years ago, U.S. Air Force pilot Chuck Yeager became the first person to fly faster than the speed of sound. Engineers have been pushing the boundaries of ultrafast flight ever since, attaining speeds most of us ...
Apr 8, 2022
1
578
Machine learning & AI
Researchers at Tampere University have successfully used artificial intelligence to predict nonlinear dynamics that take place when ultrashort light pulses interact with matter. This novel solution can be used for efficient ...
Feb 19, 2021
1
498
Computer Sciences
Autonomous functions for robots, such as spontaneity, are highly sought after. Many control mechanisms for autonomous robots are inspired by the functions of animals, including humans. Roboticists often design robot behaviors ...
Nov 11, 2020
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74
Computer Sciences
Optical illusions, images that deceive the human eye, are a fascinating research topic, as studying them can provide valuable insight into human cognition and perception. Researchers at Flinders University, in Australia, ...
Computer Sciences
Brian Mitchell and Linda Petzold, two researchers at the University of California, have recently applied model-free deep reinforcement learning to models of neural dynamics, achieving very promising results.
