As e-commerce platforms grow ever more reliant on cloud computing, efficiency and sustainability have come to the fore as urgent pressures on development. A study published in the International Journal of Reasoning-based Intelligent Systems has introduced an innovative approach to the problem based on a slime mold algorithm (SMA). The work could improve both performance and energy efficiency for e-commerce systems.As e-commerce platforms grow ever more reliant on cloud computing, efficiency and sustainability have come to the fore as urgent pressures on development. A study published in the International Journal of Reasoning-based Intelligent Systems has introduced an innovative approach to the problem based on a slime mold algorithm (SMA). The work could improve both performance and energy efficiency for e-commerce systems.[#item_full_content]

Over the past decades, computer scientists have introduced increasingly sophisticated machine learning-based models, which can perform remarkably well on various tasks. These include multimodal large language models (MLLMs), systems that can process and generate different types of data, predominantly texts, images and videos.Over the past decades, computer scientists have introduced increasingly sophisticated machine learning-based models, which can perform remarkably well on various tasks. These include multimodal large language models (MLLMs), systems that can process and generate different types of data, predominantly texts, images and videos.[#item_full_content]

Large visual collections, such as paintings, photographs, drawings, and other forms of visual media, offer valuable insights into historical events, social life, and artistic expression. These collections are key to understanding how societies produce and use images to shape cultural meaning over time. Yet they remain difficult to study due to their sheer size, often consisting of hundreds of thousands of items, and their intrinsic complexity, including diverse visual features, contents, contexts, and metadata structures.Large visual collections, such as paintings, photographs, drawings, and other forms of visual media, offer valuable insights into historical events, social life, and artistic expression. These collections are key to understanding how societies produce and use images to shape cultural meaning over time. Yet they remain difficult to study due to their sheer size, often consisting of hundreds of thousands of items, and their intrinsic complexity, including diverse visual features, contents, contexts, and metadata structures.[#item_full_content]

A new explainable AI technique transparently classifies images without compromising accuracy. The method, developed at the University of Michigan, opens up AI for situations where understanding why a decision was made is just as important as the decision itself, like medical diagnostics.A new explainable AI technique transparently classifies images without compromising accuracy. The method, developed at the University of Michigan, opens up AI for situations where understanding why a decision was made is just as important as the decision itself, like medical diagnostics.[#item_full_content]

New research from Rensselaer Polytechnic Institute (RPI) could help shape the future of artificial intelligence by making AI systems less resource-intensive, higher performing, and designed to emulate the human brain. The research was published in Patterns, titled “Dimensionality and dynamics for next-generation neural networks.”New research from Rensselaer Polytechnic Institute (RPI) could help shape the future of artificial intelligence by making AI systems less resource-intensive, higher performing, and designed to emulate the human brain. The research was published in Patterns, titled “Dimensionality and dynamics for next-generation neural networks.”[#item_full_content]

A team at Stanford has shown that using fewer, higher-quality data points can speed up complex simulations. The method could impact fields from aircraft certification to climate modeling.A team at Stanford has shown that using fewer, higher-quality data points can speed up complex simulations. The method could impact fields from aircraft certification to climate modeling.[#item_full_content]

Ready for that long-awaited summer vacation? First, you’ll need to pack all items required for your trip into a suitcase, making sure everything fits securely without crushing anything fragile.Ready for that long-awaited summer vacation? First, you’ll need to pack all items required for your trip into a suitcase, making sure everything fits securely without crushing anything fragile.[#item_full_content]

A trio of AI researchers at KAIST AI, in Korea, has developed what they call a Chain-of-Zoom framework that allows the generation of extreme super-resolution imagery using existing super-resolution models without the need for retraining.A trio of AI researchers at KAIST AI, in Korea, has developed what they call a Chain-of-Zoom framework that allows the generation of extreme super-resolution imagery using existing super-resolution models without the need for retraining.[#item_full_content]

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