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]
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.[#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.[#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.[#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.[#item_full_content]
