Self-driving cars are both fascinating and fear-inducing, as they must accurately assess and navigate the rapidly changing environment. Computer vision, which uses computation to extract information from imagery, is an important aspect of autonomous driving, with tasks ranging from low level, such as determining how far away a given location is from the vehicle, to higher level, such as determining if there is a pedestrian in the road.Self-driving cars are both fascinating and fear-inducing, as they must accurately assess and navigate the rapidly changing environment. Computer vision, which uses computation to extract information from imagery, is an important aspect of autonomous driving, with tasks ranging from low level, such as determining how far away a given location is from the vehicle, to higher level, such as determining if there is a pedestrian in the road.Automotive[#item_full_content]

A common truism among statisticians is that “the data don’t lie.” However, recent findings by Italian researchers may make those who study data think twice before making such assumptions.A common truism among statisticians is that “the data don’t lie.” However, recent findings by Italian researchers may make those who study data think twice before making such assumptions.Machine learning & AI[#item_full_content]

Advertising content generated by artificial intelligence (AI) is perceived as being of higher quality than content produced by human experts, according to a new research paper in Judgment and Decision Making.Advertising content generated by artificial intelligence (AI) is perceived as being of higher quality than content produced by human experts, according to a new research paper in Judgment and Decision Making.Business[#item_full_content]

To most effectively deliver aid to alleviate poverty, you have to know where the people most in need are. In many countries, this is often done with household surveys. But these are usually infrequent and cover limited locations.To most effectively deliver aid to alleviate poverty, you have to know where the people most in need are. In many countries, this is often done with household surveys. But these are usually infrequent and cover limited locations.Machine learning & AI[#item_full_content]

Researchers from EPFL have just released Meditron, the world’s best performing open source large language model tailored to the medical field designed to help guide clinical decision-making.Researchers from EPFL have just released Meditron, the world’s best performing open source large language model tailored to the medical field designed to help guide clinical decision-making.Computer Sciences[#item_full_content]

You’ve likely heard that “experience is the best teacher”—but what if learning in the real world is prohibitively expensive? This is the plight of roboticists training their machines on manipulation tasks. Real-world interaction data is costly, so their robots often learn from simulated versions of different activities.You’ve likely heard that “experience is the best teacher”—but what if learning in the real world is prohibitively expensive? This is the plight of roboticists training their machines on manipulation tasks. Real-world interaction data is costly, so their robots often learn from simulated versions of different activities.Robotics[#item_full_content]

To best assist humans in real-world settings, robots should be able to continuously acquire useful new skills in dynamic and rapidly changing environments. Currently, however, most robots can only tackle tasks that they have been previously trained on and can only acquire new capabilities after further training.To best assist humans in real-world settings, robots should be able to continuously acquire useful new skills in dynamic and rapidly changing environments. Currently, however, most robots can only tackle tasks that they have been previously trained on and can only acquire new capabilities after further training.Robotics[#item_full_content]

Forensic experts in the U.K. are taking new steps to identify criminals caught on CCTV using the shoes they are wearing.Forensic experts in the U.K. are taking new steps to identify criminals caught on CCTV using the shoes they are wearing.Security[#item_full_content]

Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical challenge. Shi-Ju Ran of Capital Normal University and Gang Su of the University of the Chinese Academy of Sciences have reviewed an innovative approach based on tensor networks, drawing inspiration from quantum mechanics. This approach offers a promising solution to the long-standing challenge of reconciling interpretability and efficiency in deep machine learning.Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical challenge. Shi-Ju Ran of Capital Normal University and Gang Su of the University of the Chinese Academy of Sciences have reviewed an innovative approach based on tensor networks, drawing inspiration from quantum mechanics. This approach offers a promising solution to the long-standing challenge of reconciling interpretability and efficiency in deep machine learning.Computer Sciences[#item_full_content]

Image recognition technology has come a long way since 2012 when a group of computer scientists at the University of Toronto created a convolutional neural network (CNN)—dubbed “AlexNet” after its creator Alex Krizhevsky—that correctly identified images much better than others. Its findings have propelled successful use of CNNs in related fields such as video analysis and pattern recognition, and now researchers are now focusing on 3D deep learning networks.Image recognition technology has come a long way since 2012 when a group of computer scientists at the University of Toronto created a convolutional neural network (CNN)—dubbed “AlexNet” after its creator Alex Krizhevsky—that correctly identified images much better than others. Its findings have propelled successful use of CNNs in related fields such as video analysis and pattern recognition, and now researchers are now focusing on 3D deep learning networks.Computer Sciences[#item_full_content]