Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular method involves submitting the same prompt multiple times to see if the model generates the same answer. But this method measures self-confidence, and even the most impressive LLM might be confidently wrong. Overconfidence can mislead users about the accuracy of a prediction, which might result in devastating consequences in high-stakes settings like health care or finance.Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular method involves submitting the same prompt multiple times to see if the model generates the same answer. But this method measures self-confidence, and even the most impressive LLM might be confidently wrong. Overconfidence can mislead users about the accuracy of a prediction, which might result in devastating consequences in high-stakes settings like health care or finance.[#item_full_content]

Sheepdogs, bred to control large groups of sheep in open fields, have demonstrated their skills in competitions dating back to the 1870s. In these contests, a handler directs a trained dog with whistle signals to guide a small group of sheep across a field and sometimes split the flock cleanly into two groups. But sheep do not always cooperate.Sheepdogs, bred to control large groups of sheep in open fields, have demonstrated their skills in competitions dating back to the 1870s. In these contests, a handler directs a trained dog with whistle signals to guide a small group of sheep across a field and sometimes split the flock cleanly into two groups. But sheep do not always cooperate.[#item_full_content]

Finding the right information at the right time is critical for solving complex problems. Researchers have developed an algorithm that helps individuals locate needed information more efficiently by drawing on both a user’s own history and behavioral cues, as well as the history and behavioral cues of teammates collaborating to solve the problem.Finding the right information at the right time is critical for solving complex problems. Researchers have developed an algorithm that helps individuals locate needed information more efficiently by drawing on both a user’s own history and behavioral cues, as well as the history and behavioral cues of teammates collaborating to solve the problem.[#item_full_content]

Among the primary concerns surrounding artificial intelligence is its tendency to yield erroneous information when summarizing long documents. These “hallucinations” are problematic not only because they convey falsehoods, but also because they reduce efficiency—sorting through content to search for mistakes of AI outputs is time-consuming.Among the primary concerns surrounding artificial intelligence is its tendency to yield erroneous information when summarizing long documents. These “hallucinations” are problematic not only because they convey falsehoods, but also because they reduce efficiency—sorting through content to search for mistakes of AI outputs is time-consuming.[#item_full_content]

Electrical distribution systems are characterized by dynamic operating conditions and complex network topologies, which pose significant challenges for the effective deployment of protection schemes. While impedance relays are widely used in high-voltage transmission systems, their application in medium-voltage distribution networks has been relatively limited due to operational and structural constraints.Electrical distribution systems are characterized by dynamic operating conditions and complex network topologies, which pose significant challenges for the effective deployment of protection schemes. While impedance relays are widely used in high-voltage transmission systems, their application in medium-voltage distribution networks has been relatively limited due to operational and structural constraints.[#item_full_content]

Again and again, Washington State University professor Mesut Cicek and his colleagues fed hypotheses from scientific papers into ChatGPT and asked it to determine whether the statements had been upheld by research—whether they were true or false. They did this with more than 700 hypotheses, repeating each query 10 times.Again and again, Washington State University professor Mesut Cicek and his colleagues fed hypotheses from scientific papers into ChatGPT and asked it to determine whether the statements had been upheld by research—whether they were true or false. They did this with more than 700 hypotheses, repeating each query 10 times.[#item_full_content]

New research published in Machine Learning shows pattern learning is not enough to train AI to tackle games—and abstract representations or hybrid approaches may help. Many AI researchers describe game-playing as the “Formula 1” of AI: it’s a controlled test environment with clear rules and clear success criteria. This paper uses that idea as a diagnostic, by studying a very simple game Nim, a children’s matchstick game whose optimal strategy is known exactly.New research published in Machine Learning shows pattern learning is not enough to train AI to tackle games—and abstract representations or hybrid approaches may help. Many AI researchers describe game-playing as the “Formula 1” of AI: it’s a controlled test environment with clear rules and clear success criteria. This paper uses that idea as a diagnostic, by studying a very simple game Nim, a children’s matchstick game whose optimal strategy is known exactly.[#item_full_content]

Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that compute shortest paths through vast networks. Now imagine scaling that task to calculate distances between every pair of points in a massive system, for example, a transportation grid, a communication backbone, or even a biological network such as protein or neural interaction networks.Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that compute shortest paths through vast networks. Now imagine scaling that task to calculate distances between every pair of points in a massive system, for example, a transportation grid, a communication backbone, or even a biological network such as protein or neural interaction networks.[#item_full_content]

Over the past decades, computer scientists have developed numerous artificial intelligence (AI) systems that can process human speech in different languages. The extent to which these models replicate the brain processes via which humans understand spoken language, however, has not yet been clearly determined.Over the past decades, computer scientists have developed numerous artificial intelligence (AI) systems that can process human speech in different languages. The extent to which these models replicate the brain processes via which humans understand spoken language, however, has not yet been clearly determined.[#item_full_content]

AI chatbots are standardizing how people speak, write, and think. If this homogenization continues unchecked, it risks reducing humanity’s collective wisdom and ability to adapt, computer scientists and psychologists argue in an opinion paper published in Trends in Cognitive Sciences.AI chatbots are standardizing how people speak, write, and think. If this homogenization continues unchecked, it risks reducing humanity’s collective wisdom and ability to adapt, computer scientists and psychologists argue in an opinion paper published in Trends in Cognitive Sciences.[#item_full_content]