Researchers at the Institute of Information Security at Graz University of Technology (TU Graz) have uncovered security risks in the file notification systems of the widely used operating systems Windows, Linux, Android and macOS. Through side-channel attacks, attackers can track system-wide changes to files, keystrokes and visited websites, and spoof password prompts to intercept entries.
Before a new AI model reaches the public, its developers run it through a battery of tests known as "benchmarks," which score it on everything from reasoning ability to how safe it is for people to use. Billions of investment dollars ride on these benchmark scores, and policymakers increasingly cite them to shape regulations and government procurement decisions that will guide the development of AI.
A new AI system that excels at challenging games with hidden information could someday help human decision-makers select strategies to outfox opponents in complicated situations like military maneuvers.
In the production of video games and animated movies, directors and animators are constantly fine-tuning how a character's movements should appear. In many cases, directors require subtle changes, such as making a character appear a little more restrained or a bit more expressive, and communicate subjectively how much change is needed.
Interactions between humans and dogs involve a continuous exchange of physical and verbal cues. A person may pet a dog, use a hand gesture, give a verbal command or call the pet from a distance, prompting changes in the dog's posture, position or movement. Understanding these human–animal interactions requires data that captures both participants simultaneously.
Researchers from Tokyo Metropolitan University have used an evolutionary algorithm to identify optimal shapes for ultra-thin, bio-inspired corrugated airfoils, the two-dimensional cut-throughs of wings. Lightweight membrane-like wings are a strong contender for use in unmanned aerial vehicles (UAVs) in thin atmospheres, like on Mars, and in UAV miniaturization.
For decades, the gold standard for capturing human movement and transferring these data into the digital world has required actors to wear suits with physical markers that cameras track in a specialized studio. While accurate, this capture process is time-consuming and expensive. Markers need to be placed manually, they can fall off, and if two people get too close—such as during a hug or a dance—the system fails to track all markers as one person blocks the other from the camera's view, and accuracy drops significantly. Extensive post-processing is needed to recover the motion in such challenging sequences. The creators of the Hollywood blockbusters "Avatar" or "The Lord of the Rings" will know what we mean.
A research team at the Faculty of Engineering at The University of Hong Kong (HKU), led by professor Ruibang Luo of the School of Computing and Data Science and professor Can Li of the Department of Electrical and Computer Engineering, has developed Gungnir, a blockchain-inspired DNA data storage codec. The framework improves digital information recovery from severely damaged DNA sequences, potentially extending the practical lifespan of DNA data archives from less than a decade to centuries. The paper is published in the journal Nature Communications.
Artificial intelligence models can give users the wrong answer and do so with great confidence. They can also hedge and warn that they are unsure—even when they get the answer right.
William Overman began his Ph.D. program at Stanford Graduate School of Business at an auspicious moment: just two months before ChatGPT launched publicly in November 2022, exploding the widely held understanding of what machines are capable of.
MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems. In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical or task-specific requirements, known as hard constraints.
Artificial intelligence (AI) systems, particularly the large language models (LLMs) that underpin ChatGPT and similar platforms, are remarkably skilled at answering queries about a wide range of topics. However, the extent to which they can interpret social situations and predict how humans might respond in specific scenarios remains poorly understood.
Large language models (LLMs), the artificial intelligence (AI) systems supporting the functioning of ChatGPT, Gemini and similar conversational platforms, are often expected to answer queries, generate texts for specific purposes and make decisions without the supervision of human experts. Yet past studies suggest that these models can sometimes mislead users, producing unreliable answers that express high confidence in false or inaccurate statements.
Researchers at Maynooth University (MU) have developed a first-of-its-kind DNA computer, described as one of the most complex and fastest molecular computers yet reported.
MIT researchers have created a computing platform that could be used to develop intelligent and adaptive next-generation electronics that can perform multiple functions, like computing and memory, within one extremely compact, energy-efficient device.
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