news

New miniature laboratories are ensuring that artificial intelligence (AI) doesn't make mistakes. They provide a controlled test environment where algorithms and AI models can be checked before being put to work under real-life conditions. The aim is for AI to work reliably. Anyone who develops an AI solution sometimes goes on a journey into the unknown.

Neat lanes are the norm at road crossings - until people start veering off at critical angles, then chaos ensues. Zebra crossings generally showcase the best in pedestrian behaviour, with people naturally forming orderly lanes as they cross the road, smoothly passing those coming from the opposite direction without any bumps or scrapes.

Until now, physics has differentiated between fermions and bosons, but now there is evidence of a third type of particle At first glance, our world appears to be enormously complex. However, according to the laws of particle physics, it is strictly organised. According to this, there are only two classes of particles, the matter particles and the force particles.

Until now, physics has distinguished between fermions and bosons, but now there are indications of a third type of particle At first glance, our world appears to be enormously complex. However, according to the laws of particle physics, it is strictly ordered. According to this, there are only two classes of particles, the matter particles and the force particles.

Researchers at Radboud University have developed a new method to calculate the reliability of the power grid. This new method, based on Graph Neural Networks, is not only a thousand times faster but also more accurate than current methods. The results of the new method have been published in the journal Applied Energy.

Scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and conditions. In the parable of the blind men and the elephant, several blind men each describe a different part of an elephant they are touching - a sharp tusk, a flexible trunk, or a broad leg - and disagree about the animal's true nature.

Is there a contradiction between quantum theory and thermodynamics? On the surface, yes - but at TU Wien, researchers have now shown how the two fit together perfectly. It is one of the most important laws of nature that we know: The famous second law of thermodynamics says that the world gets more and more disordered, when random chance is at play.

The reproduction number R is often used as an indicator to predict how quickly an infectious disease will spread. researchers have developed a mathematical model that is just as easy to use but enables more accurate predictions than R. Their model is based on a reproduction matrix that takes into account the heterogeneity of society.

Western researchers have developed a novel technique using math to understand exactly how neural networks make decisions - a widely recognized but poorly understood process in the field of machine learning. Many of today's technologies, from digital assistants like Siri and ChatGPT to medical imaging and self-driving cars, are powered by machine learning.

Scientists have developed a new mathematical model to help people understand the risks posed by AI and assist regulators in protecting privacy. AI tools are increasingly being used to track and monitor people both online and in person, posing challenges for anonymity and privacy. For example, AI tools are being trialled to automatically identify individuals from their voices in online banking, their eyes in humanitarian aid delivery, or their faces in law enforcement.

AI tools are increasingly being used to track and monitor us both online and in-person, yet their effectiveness comes with big risks. Computer scientists at the University of Oxford have led a study to develop a new mathematical model which could help people better understand the risks posed by AI and assist regulators in protecting peoples' privacy.

Helping out your neighbor or minding your own business? A challenging choice with different benefits for each decision. Game theory provides guidance in making such choices - from a theoretical perspective. Novel findings by Jakub Svoboda and Krishnendu Chatterjee at the Institute of Science and Technology Austria (ISTA) reveal new network structures that enhance cooperation throughout a system.

What can exploding stars teach us about how blood flows through an artery' Or swimming bacteria about how the ocean's layers mix' A collaboration of researchers, including from the University of Cambridge, has reached a milestone toward training artificial intelligence models to find and use transferable knowledge between fields to drive scientific discovery.

Scientist from the Cluster of Excellence Mathematics Münster proves conjecture from physics String theory aims to explain all fundamental forces and particles in the universe - essentially, how the world operates on the smallest scales. Though it has not yet been experimentally verified, work in string theory has already led to significant advancements in mathematics and theoretical physics.

An AI method developed by Professor Markus Buehler finds hidden links between science and art to suggest novel materials. Imagine using artificial intelligence to compare two seemingly unrelated creations - biological tissue and Beethoven's "Symphony No. 9." At first glance, a living system and a musical masterpiece might appear to have no connection.

ISTA researchers investigate why graph isomorphism algorithms seem to be so effective Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a public transportation network. Mathematicians have long sought to develop algorithms that can compare any two graphs.

Cause and effect. We understand this concept from an early age. Tug on a pull toy's string, and the toy follows. Naturally, things get much more complicated as a system grows, as the number of variables increases, and as noise enters the picture. Eventually, it can become almost impossible to tell whether a variable is causing an effect or is simply correlated or associated with it.

Engineers at EPFL and ETH Zurich have come up with a new approach for reducing traffic congestion in large cities during rush hour. Their system is designed to be both fair and effective. Rush-hour traffic congestion is a major headache for commuters and a real problem for city planners. Worldwide, a huge amount of time is wasted stuck in traffic.

MIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy. Imagine you're tasked with sending a team of football players onto a field to assess the condition of the grass (a likely task for them, of course). If you pick their positions randomly, they might cluster together in some areas while completely neglecting others.

The technique leverages quantum properties of light to guarantee security while preserving the accuracy of a deep-learning model. Deep-learning models are being used in many fields, from health care diagnostics to financial forecasting. However, these models are so computationally intensive that they require the use of powerful cloud-based servers.