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.[#item_full_content]

Imagine you are in a vast library with no catalog, typing random words into a search bar and hoping to stumble upon the exact book you need. That has been the reality for many roboticists trying to find the right ROS (Robot Operating System) package. With over 7,500 options available, keyword searches often return irrelevant results, wasting developers’ precious time and energy.Imagine you are in a vast library with no catalog, typing random words into a search bar and hoping to stumble upon the exact book you need. That has been the reality for many roboticists trying to find the right ROS (Robot Operating System) package. With over 7,500 options available, keyword searches often return irrelevant results, wasting developers’ precious time and energy.[#item_full_content]

Will algorithms designed for interconnected computers hold up if some of the machines are not here on Earth but flying about in space, onboard satellites or spacecraft?Will algorithms designed for interconnected computers hold up if some of the machines are not here on Earth but flying about in space, onboard satellites or spacecraft?[#item_full_content]

At the dawn of computing, women were the early adopters of computational technology, working with punch cards in what was then considered secretarial work. As computer science evolved into a prestigious field focused on algorithms and theory, women became—and remained—underrepresented. Today, only 23% of bachelor’s and doctoral degrees in computer science are awarded to women, and just 18% of full professors are women—fewer than in the 1980s.At the dawn of computing, women were the early adopters of computational technology, working with punch cards in what was then considered secretarial work. As computer science evolved into a prestigious field focused on algorithms and theory, women became—and remained—underrepresented. Today, only 23% of bachelor’s and doctoral degrees in computer science are awarded to women, and just 18% of full professors are women—fewer than in the 1980s.[#item_full_content]

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]