Research has shown that large language models (LLMs) tend to overemphasize information at the beginning and end of a document or conversation, while neglecting the middle.Research has shown that large language models (LLMs) tend to overemphasize information at the beginning and end of a document or conversation, while neglecting the middle.[#item_full_content]

Today’s generative artificial intelligence models can create everything from images to computer applications, but the quality of their output depends largely on the prompt a human user provides.Today’s generative artificial intelligence models can create everything from images to computer applications, but the quality of their output depends largely on the prompt a human user provides.[#item_full_content]

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]

Products ranging from footwear to AI counterfeit detectors fill the halls of Paris’s Vivatech trade fair, which runs until Saturday.Products ranging from footwear to AI counterfeit detectors fill the halls of Paris’s Vivatech trade fair, which runs until Saturday.[#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]

Animators could create more realistic bouncy, stretchy, and squishy characters for movies and video games thanks to a new simulation method developed by researchers at MIT.Animators could create more realistic bouncy, stretchy, and squishy characters for movies and video games thanks to a new simulation method developed by researchers at MIT.[#item_full_content]