Researchers in Japan have invented a novel method to measure the permittivity of insulators 100 times more accurately than before. This technology is expected to contribute to the efficient development of sensitive radio receivers for radio telescopes as well as to the development of devices for the next generation communication networks, “Beyond 5G/6G.”Researchers in Japan have invented a novel method to measure the permittivity of insulators 100 times more accurately than before. This technology is expected to contribute to the efficient development of sensitive radio receivers for radio telescopes as well as to the development of devices for the next generation communication networks, “Beyond 5G/6G.”[#item_full_content]
University of Waterloo researchers have developed a new explainable artificial intelligence (AI) model to reduce bias and enhance trust and accuracy in machine learning-generated decision-making and knowledge organization.University of Waterloo researchers have developed a new explainable artificial intelligence (AI) model to reduce bias and enhance trust and accuracy in machine learning-generated decision-making and knowledge organization.[#item_full_content]
University of Waterloo researchers have developed a new explainable artificial intelligence (AI) model to reduce bias and enhance trust and accuracy in machine learning-generated decision-making and knowledge organization.University of Waterloo researchers have developed a new explainable artificial intelligence (AI) model to reduce bias and enhance trust and accuracy in machine learning-generated decision-making and knowledge organization.Computer Sciences[#item_full_content]
Sea turtles can glide majestically through ocean waters and maneuver like armored vehicles over rocks and sand on land. Their locomotive adaptability makes them particularly interesting to robotics experts, who seek to learn the secrets of their gait and propulsion.Sea turtles can glide majestically through ocean waters and maneuver like armored vehicles over rocks and sand on land. Their locomotive adaptability makes them particularly interesting to robotics experts, who seek to learn the secrets of their gait and propulsion.[#item_full_content]
An AI-infused future has tremendous promise in virtually all aspects of our lives from medicine to education, industry to finance.An AI-infused future has tremendous promise in virtually all aspects of our lives from medicine to education, industry to finance.[#item_full_content]
An AI-infused future has tremendous promise in virtually all aspects of our lives from medicine to education, industry to finance.An AI-infused future has tremendous promise in virtually all aspects of our lives from medicine to education, industry to finance.Computer Sciences[#item_full_content]
Researchers from the UCLA Samueli School of Engineering have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data.Researchers from the UCLA Samueli School of Engineering have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data.[#item_full_content]
Researchers from the UCLA Samueli School of Engineering have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data.Researchers from the UCLA Samueli School of Engineering have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data.Computer Sciences[#item_full_content]
Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid algorithm. They tested their algorithm in three application scenarios: data denoising, scene background extraction, and fluid dynamics analysis. They determined that it can operate with only a small number of samples and has a quantum advantage in the analysis of high-dimensional time series.Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid algorithm. They tested their algorithm in three application scenarios: data denoising, scene background extraction, and fluid dynamics analysis. They determined that it can operate with only a small number of samples and has a quantum advantage in the analysis of high-dimensional time series.[#item_full_content]
Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid algorithm. They tested their algorithm in three application scenarios: data denoising, scene background extraction, and fluid dynamics analysis. They determined that it can operate with only a small number of samples and has a quantum advantage in the analysis of high-dimensional time series.Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid algorithm. They tested their algorithm in three application scenarios: data denoising, scene background extraction, and fluid dynamics analysis. They determined that it can operate with only a small number of samples and has a quantum advantage in the analysis of high-dimensional time series.Computer Sciences[#item_full_content]
