BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the Institute of Science Tokyo, Japan. This breakthrough framework utilizes an innovative cross-partition message quantization technique and a novel training algorithm to significantly reduce memory demands and increase computational and energy efficiency.BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the Institute of Science Tokyo, Japan. This breakthrough framework utilizes an innovative cross-partition message quantization technique and a novel training algorithm to significantly reduce memory demands and increase computational and energy efficiency.Hardware[#item_full_content]

Images generated by artificial intelligence (AI) are often almost indistinguishable from real images to the human eye. Watermarks—visible or invisible markers embedded in image files—may be the key to verifying whether an image was generated by AI. So-called semantic watermarks, which are embedded deep within the image generation process itself, are considered to be especially robust and hard to remove.Images generated by artificial intelligence (AI) are often almost indistinguishable from real images to the human eye. Watermarks—visible or invisible markers embedded in image files—may be the key to verifying whether an image was generated by AI. So-called semantic watermarks, which are embedded deep within the image generation process itself, are considered to be especially robust and hard to remove.Security[#item_full_content]

While there’s been much negative discussion about AI, including about the possibility that it will take over the world, the public is also being bombarded with positive messages about the technology, and what it can do.While there’s been much negative discussion about AI, including about the possibility that it will take over the world, the public is also being bombarded with positive messages about the technology, and what it can do.Business[#item_full_content]

New partnerships are forming between tech companies and power operators—ones that could reshape decades of misconceptions about nuclear energy.New partnerships are forming between tech companies and power operators—ones that could reshape decades of misconceptions about nuclear energy.Energy & Green Tech[#item_full_content]

Artificial intelligence (AI) is quietly transforming how cities generate, store and distribute energy, acting as the invisible conductor that orchestrates cleaner, smarter and more resilient cities.Artificial intelligence (AI) is quietly transforming how cities generate, store and distribute energy, acting as the invisible conductor that orchestrates cleaner, smarter and more resilient cities.Energy & Green Tech[#item_full_content]

The use of AI is spreading throughout all professions and industries—and law is no exception.The use of AI is spreading throughout all professions and industries—and law is no exception.Machine learning & AI[#item_full_content]

Recently, text-based image generation models can automatically create high-resolution, high-quality images solely from natural language descriptions. However, when a typical example like the Stable Diffusion model is given the text “creative,” its ability to generate truly creative images remains limited.Recently, text-based image generation models can automatically create high-resolution, high-quality images solely from natural language descriptions. However, when a typical example like the Stable Diffusion model is given the text “creative,” its ability to generate truly creative images remains limited.Computer Sciences[#item_full_content]

Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI-like chatbots so good at understanding and using words. The work is published in the journal Physical Review X.Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI-like chatbots so good at understanding and using words. The work is published in the journal Physical Review X.Computer Sciences[#item_full_content]

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a result, in addition to tackling various real-world computational problems, they could help neuroscientists and psychologists to better understand the underpinnings of specific sensory or cognitive processes.Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a result, in addition to tackling various real-world computational problems, they could help neuroscientists and psychologists to better understand the underpinnings of specific sensory or cognitive processes.Machine learning & AI[#item_full_content]

At Brown University, an innovative new project is revealing that teaching artificial intelligence to perceive things more like people may begin with something as simple as a game. The project invites participants to play an online game called Click Me, which helps AI models learn how people see and interpret images. While the game is fun and accessible, its purpose is more ambitious: to understand the root causes of AI errors and to systematically improve how AI systems represent the visual world.At Brown University, an innovative new project is revealing that teaching artificial intelligence to perceive things more like people may begin with something as simple as a game. The project invites participants to play an online game called Click Me, which helps AI models learn how people see and interpret images. While the game is fun and accessible, its purpose is more ambitious: to understand the root causes of AI errors and to systematically improve how AI systems represent the visual world.Machine learning & AI[#item_full_content]