Researchers in Japan have developed quantum multi-programming auto mode, a function that automatically runs quantum programs from different users in parallel. Launched on the Center for Quantum Information and Quantum Biology (QIQB) quantum computer cloud service at the University of Osaka, the system reduces idle qubit resources, improves throughput and may help ease congestion in quantum cloud computing.
To accelerate and refine decision-making in a fast-paced, global marketplace, enterprises may deploy generative artificial intelligence models to help summarize and interpret the charts that often fill market summaries and financial reports.
Some people have a gift for creating beautiful works of art. Others appreciate art but do not have the talent to create it. Researchers at Cornell Tech and the Cornell Bowers College of Computing and Information Science have created an artificial intelligence framework, ShadowDraw, that can create "shadow art"—partial line drawings that are completed by the shadow cast from an object—by simply scanning the object.
Giving AI a classic psychological test reveals an inherent weakness in LLM decision-making abilities. Suketu Patel and colleagues explored how transformer-based machine attention differs from human attention by testing AI models on the "Stroop task," in which words for colors are printed in colored ink, and participants are asked to name the ink color of each word while ignoring its meaning.
Artificial intelligence (AI)-generated images have become increasingly more sophisticated than early ones that showed humans with more than five fingers on a hand, making it even harder to determine whether photos are authentic. Now, a team of computer scientists in the McKelvey School of Engineering at Washington University in St. Louis has developed a model that can detect fake images by learning which are real.
In a bustling restaurant kitchen, efficiency requires more than just machines that wash dishes or chop vegetables. It requires a conductor to ensure the appetizer, main course, and dessert are prepared in the right sequence, that the right chef gets the right order, and that the correct dish reaches the right table on time.
In a study published in IEEE Transactions on Software Engineering, researchers from Kyushu University have found that "flaky tests," which are unstable software tests that seem to randomly pass or fail, do not stay confined to the projects they originate in and often spread across entire ecosystems.
When people watch a scene in the film "Jurassic Park" where a giant dinosaur walks toward them, they naturally imagine a heavy, rumbling sound, as if the ground were shaking. This is because humans predict sound by considering not only the shape of an object, but also physical properties such as its size, weight, and speed of movement. However, existing video-to-audio generation AI mainly generates sound based on the category of objects or scene information in the video, and has not sufficiently reflected physical properties that vary depending on weight or speed.
New research from the University of the Witwatersrand, South Africa, has significant implications for understanding both human language development and the behavior of large-scale artificial intelligence language models.
New research by Brown University computer scientists may be a key step in bringing volumetric video—video that can be viewed from virtually any perspective in a 3D scene—to computers and smart televisions.
New work explaining the inner workings of artificial intelligence could provide a way around the threat of AI "model collapse," potentially averting growing numbers of AI hallucinations in the future.
Computer scientists at UC Riverside have identified troubling flaws in a new generation of artificial intelligence (AI) agents designed to take over routine computer chores while users are away—sorting emails, organizing files, analyzing data, and handling other everyday digital tasks that might otherwise consume hours.
Today, artificial intelligence can describe images, recognize objects, and explain complex relationships. The pace of development is remarkable: So-called vision-language models (VLMs) combine text and image understanding in impressive ways. Yet, of all things, they struggle with a seemingly simple task—counting. Researchers at the Institute for Information Systems (iisys) at Hof University of Applied Sciences are now working to address this issue, with a paper posted to the arXiv preprint server.
Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily powerful, yet their internal workings remain largely a "black box." To better understand how these systems produce their responses, a group of physicists at Harvard University has developed a simplified mathematical model of learning in neural networks that can be analyzed mathematically using the tools of statistical physics.
Researchers from MIT and elsewhere have developed a more user-friendly and efficient method to help networking engineers identify potential system failures before they cause major problems, like a cloud service outage that leaves millions of users unable to access applications.
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