The promise of smart wearables is often talked up, and while there have been some impressive innovations, we are still not seeing their full potential. Among the things holding them back is that the chips that operate them are stiff, brittle, and power-hungry. To overcome these problems, researchers from Tsinghua University and Peking University in China have developed FLEXI, a new family of flexible chips. They are thinner than a human hair, flexible enough to be folded thousands of times, and incorporate AI.The promise of smart wearables is often talked up, and while there have been some impressive innovations, we are still not seeing their full potential. Among the things holding them back is that the chips that operate them are stiff, brittle, and power-hungry. To overcome these problems, researchers from Tsinghua University and Peking University in China have developed FLEXI, a new family of flexible chips. They are thinner than a human hair, flexible enough to be folded thousands of times, and incorporate AI.Electronics & Semiconductors[#item_full_content]

Federal and state governments have outlawed “revenge porn,” the nonconsensual online sharing of sexual images of individuals, often by former partners. Last year, South Carolina became the 50th state to enact such a law. The recent rise of easy-to-use generative AI tools, however, has introduced a new wrinkle: What happens when those images look real but have been created by AI? What’s lawful in the U.S. and who’s responsible is not yet clear.Federal and state governments have outlawed “revenge porn,” the nonconsensual online sharing of sexual images of individuals, often by former partners. Last year, South Carolina became the 50th state to enact such a law. The recent rise of easy-to-use generative AI tools, however, has introduced a new wrinkle: What happens when those images look real but have been created by AI? What’s lawful in the U.S. and who’s responsible is not yet clear.Business[#item_full_content]

Meta Platforms Inc.’s better-than-expected sales outlook helped ease Wall Street concerns about plans for unprecedented spending on artificial intelligence this year. The social networking giant topped projections for holiday quarter revenue and gave a strong forecast for the current period during its earnings report on Jan. 28. Improvements in its online advertising business are making it possible for Meta to spend hundreds of billions of dollars over the next few years on AI infrastructure. Meta’s shares jumped more than 11% in extended trading.Meta Platforms Inc.’s better-than-expected sales outlook helped ease Wall Street concerns about plans for unprecedented spending on artificial intelligence this year. The social networking giant topped projections for holiday quarter revenue and gave a strong forecast for the current period during its earnings report on Jan. 28. Improvements in its online advertising business are making it possible for Meta to spend hundreds of billions of dollars over the next few years on AI infrastructure. Meta’s shares jumped more than 11% in extended trading.Business[#item_full_content]

Over the past decades, computer scientists have developed increasingly advanced artificial intelligence (AI) systems that perform well on various tasks, including the analysis or generation of images, videos, audio recordings and texts. These systems power various highly performing software, including automated transcription apps, large language model (LLM)-powered conversational agents like ChatGPT, and various other platforms.Over the past decades, computer scientists have developed increasingly advanced artificial intelligence (AI) systems that perform well on various tasks, including the analysis or generation of images, videos, audio recordings and texts. These systems power various highly performing software, including automated transcription apps, large language model (LLM)-powered conversational agents like ChatGPT, and various other platforms.Electronics & Semiconductors[#item_full_content]

People can develop emotional closeness to artificial intelligence (AI)—under certain conditions, even more so than to other people. This is shown by a new study conducted by a research team led by Prof. Dr. Markus Heinrichs and Dr. Tobias Kleinert from the Department of Psychology at the University of Freiburg and Prof. Dr. Bastian Schiller from Heidelberg University’s Institute of Psychology. Participants felt a sense of closeness especially when they did not know that they were communicating with AI. The results have been published in Communications Psychology.People can develop emotional closeness to artificial intelligence (AI)—under certain conditions, even more so than to other people. This is shown by a new study conducted by a research team led by Prof. Dr. Markus Heinrichs and Dr. Tobias Kleinert from the Department of Psychology at the University of Freiburg and Prof. Dr. Bastian Schiller from Heidelberg University’s Institute of Psychology. Participants felt a sense of closeness especially when they did not know that they were communicating with AI. The results have been published in Communications Psychology.Consumer & Gadgets[#item_full_content]

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective at capturing relationships between nodes and edges in data, but often overlook higher-order, complex connections. To address this challenge, a research team at The Hong Kong Polytechnic University (PolyU) has developed a new heterogeneous graph attention network, revolutionizing the modeling of complex relationships in graph-structured data. This innovation is poised to break through AI application limitations in fields such as neuroscience, logistics, computer vision and biology.As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective at capturing relationships between nodes and edges in data, but often overlook higher-order, complex connections. To address this challenge, a research team at The Hong Kong Polytechnic University (PolyU) has developed a new heterogeneous graph attention network, revolutionizing the modeling of complex relationships in graph-structured data. This innovation is poised to break through AI application limitations in fields such as neuroscience, logistics, computer vision and biology.Machine learning & AI[#item_full_content]

Penn Engineers have developed a novel design for solar-powered data centers that will orbit Earth and could realistically scale to meet the growing demand for AI computing while reducing the environmental impact of data centers.Penn Engineers have developed a novel design for solar-powered data centers that will orbit Earth and could realistically scale to meet the growing demand for AI computing while reducing the environmental impact of data centers.Energy & Green Tech[#item_full_content]

EU lawmakers on Wednesday demanded artificial intelligence providers pay for their use of copyrighted European content as they called for expanded rules to apply to generative AI.EU lawmakers on Wednesday demanded artificial intelligence providers pay for their use of copyrighted European content as they called for expanded rules to apply to generative AI.Machine learning & AI[#item_full_content]

Large language models (LLMs), artificial intelligence (AI) systems that can process and generate texts in various languages, are now widely used by people worldwide. These models have proved to be effective in rapidly sourcing information, answering questions, creating written content for specific applications and writing computer code.Large language models (LLMs), artificial intelligence (AI) systems that can process and generate texts in various languages, are now widely used by people worldwide. These models have proved to be effective in rapidly sourcing information, answering questions, creating written content for specific applications and writing computer code.Computer Sciences[#item_full_content]

When Daniel Graham, an associate professor in the University of Virginia School of Data Science, talks about the future of intelligent systems, he does not begin with the usual vocabulary of cybersecurity or threat mitigation. Instead, he focuses on quality assurance and on how to build digital and physical systems we can trust.When Daniel Graham, an associate professor in the University of Virginia School of Data Science, talks about the future of intelligent systems, he does not begin with the usual vocabulary of cybersecurity or threat mitigation. Instead, he focuses on quality assurance and on how to build digital and physical systems we can trust.Security[#item_full_content]