The emergence of so-called deepfake technology, which commonly involves the generation of fake images, video, and sound that seem so authentic as to confuse even expert viewers and listeners, is at the point where it can influence important aspects of our lives, such as politics, finance, and beyond.The emergence of so-called deepfake technology, which commonly involves the generation of fake images, video, and sound that seem so authentic as to confuse even expert viewers and listeners, is at the point where it can influence important aspects of our lives, such as politics, finance, and beyond.[#item_full_content]

A trio of computer scientists at Auburn University, in the U.S., working with a colleague from the University of Alberta, in Canada, has found that claims of visual skills by large language models (LLMs) with vision capabilities (VLMs) may be overstating abilities.A trio of computer scientists at Auburn University, in the U.S., working with a colleague from the University of Alberta, in Canada, has found that claims of visual skills by large language models (LLMs) with vision capabilities (VLMs) may be overstating abilities.[#item_full_content]

When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of large language models (LLMs) stems from their vast size, complex training methods, hard-to-predict behaviors, and elusive interpretability.When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of large language models (LLMs) stems from their vast size, complex training methods, hard-to-predict behaviors, and elusive interpretability.[#item_full_content]

Researchers at the Artificial Intelligence and Machine Learning Lab (AIML) in the Department of Computer Science at TU Darmstadt and the Hessian Center for Artificial Intelligence (hessian.AI) have developed a method that uses vision language models to filter, evaluate, and suppress specific image content in large datasets or from image generators.Researchers at the Artificial Intelligence and Machine Learning Lab (AIML) in the Department of Computer Science at TU Darmstadt and the Hessian Center for Artificial Intelligence (hessian.AI) have developed a method that uses vision language models to filter, evaluate, and suppress specific image content in large datasets or from image generators.[#item_full_content]

Humanoids, robotic or virtual systems with body structures that resemble the human body, have a wide range of real-world applications. As their limbs and bodies mirror those of humans, they could be made to reproduce a wide range of human movements, such as walking, crouching, jumping, swimming and so on.Humanoids, robotic or virtual systems with body structures that resemble the human body, have a wide range of real-world applications. As their limbs and bodies mirror those of humans, they could be made to reproduce a wide range of human movements, such as walking, crouching, jumping, swimming and so on.[#item_full_content]

A new study introduces a user preference mining algorithm that leverages data mining and social behavior analysis to bolster brand building efforts. This innovative approach aims to assist small and medium-sized enterprises (SMEs) in understanding and engaging with their consumer base more effectively.A new study introduces a user preference mining algorithm that leverages data mining and social behavior analysis to bolster brand building efforts. This innovative approach aims to assist small and medium-sized enterprises (SMEs) in understanding and engaging with their consumer base more effectively.[#item_full_content]

Small teams—no matter the project they are working on—are constantly sharing information with each other about goals, obstacles and next steps. By talking through options, the group builds a shared understanding of the work. It’s a complicated and decidedly human process that can get messy quickly if one member is not paying attention or simply misunderstands a key point and fails to clarify it while the group pushes forward.Small teams—no matter the project they are working on—are constantly sharing information with each other about goals, obstacles and next steps. By talking through options, the group builds a shared understanding of the work. It’s a complicated and decidedly human process that can get messy quickly if one member is not paying attention or simply misunderstands a key point and fails to clarify it while the group pushes forward.[#item_full_content]

The security of traditional attribute-based searchable encryption schemes relies on traditional number-theoretic assumptions, and thus they are not able to resist the threat of quantum algorithms. Existing lattice-based searchable encryption schemes have two main problems: one is the low efficiency of the execution of encryption, key generation and search algorithms. The second is the large space required for storing search trapdoors.The security of traditional attribute-based searchable encryption schemes relies on traditional number-theoretic assumptions, and thus they are not able to resist the threat of quantum algorithms. Existing lattice-based searchable encryption schemes have two main problems: one is the low efficiency of the execution of encryption, key generation and search algorithms. The second is the large space required for storing search trapdoors.[#item_full_content]

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