Experts have shown that the most powerful security defenses in Windows 11 can be dismantled by an attacker who never touches the target computer.Experts have shown that the most powerful security defenses in Windows 11 can be dismantled by an attacker who never touches the target computer.[#item_full_content]

In the animal kingdom, energy conservation is essential for survival. That’s why our brains have evolved to be extremely energy- and resource-efficient at storing and processing information. Since the 1980s, computational scientists have tried to mimic brain structure and function in the hopes of achieving such efficient, fast processing of complex data.In the animal kingdom, energy conservation is essential for survival. That’s why our brains have evolved to be extremely energy- and resource-efficient at storing and processing information. Since the 1980s, computational scientists have tried to mimic brain structure and function in the hopes of achieving such efficient, fast processing of complex data.[#item_full_content]

The COVID-19 pandemic changed the way many people approached their work across the globe. For Carnegie Mellon University Africa’s Jema Ndibwile, it changed the way he viewed a completely different type of virus: a computer virus.The COVID-19 pandemic changed the way many people approached their work across the globe. For Carnegie Mellon University Africa’s Jema Ndibwile, it changed the way he viewed a completely different type of virus: a computer virus.[#item_full_content]

McGill University researchers have developed a more energy-efficient method of building AI systems that are better at measuring—and indicating—their own uncertainty. This will help users determine when human oversight is needed, when additional data should be collected and when a model is being asked to work beyond the conditions it was trained for, the researchers said.McGill University researchers have developed a more energy-efficient method of building AI systems that are better at measuring—and indicating—their own uncertainty. This will help users determine when human oversight is needed, when additional data should be collected and when a model is being asked to work beyond the conditions it was trained for, the researchers said.[#item_full_content]

Researchers from Skoltech (part of the VEB.RF group) and Central University have developed an automated coin-grading approach that minimizes the subjectivity of manual assessments and overcomes the limitations of computer vision algorithms typically used for this purpose. The new approach provides more accurate and detailed grading across a wide variety of coin types. The approach was presented in the Journal on Computing and Cultural Heritage and further refined in two subsequent studies published in Expert Systems with Applications and IEEE Transactions on Instrumentation and Measurement.Researchers from Skoltech (part of the VEB.RF group) and Central University have developed an automated coin-grading approach that minimizes the subjectivity of manual assessments and overcomes the limitations of computer vision algorithms typically used for this purpose. The new approach provides more accurate and detailed grading across a wide variety of coin types. The approach was presented in the Journal on Computing and Cultural Heritage and further refined in two subsequent studies published in Expert Systems with Applications and IEEE Transactions on Instrumentation and Measurement.[#item_full_content]

From searching disaster zones and responding to chemical spills to monitoring fragile ecosystems, future robot swarms may have to act in places where direct human control is difficult or dangerous. To operate autonomously, the robots must be able to decide together which problem to address and where to go next. But collective decision-making creates its own vulnerability: Robots improve their decisions by sharing information, yet faulty machines, inaccurate observations or manipulated messages can mislead the entire swarm.From searching disaster zones and responding to chemical spills to monitoring fragile ecosystems, future robot swarms may have to act in places where direct human control is difficult or dangerous. To operate autonomously, the robots must be able to decide together which problem to address and where to go next. But collective decision-making creates its own vulnerability: Robots improve their decisions by sharing information, yet faulty machines, inaccurate observations or manipulated messages can mislead the entire swarm.[#item_full_content]

On a sunny summer’s day, children build sandcastles on the beach. But behind every castle and crumbling dune lies a surprisingly difficult scientific problem. In fact, the physics of sand is not yet fully understood—which also means that computer graphics lacks effective ways to simulate it.On a sunny summer’s day, children build sandcastles on the beach. But behind every castle and crumbling dune lies a surprisingly difficult scientific problem. In fact, the physics of sand is not yet fully understood—which also means that computer graphics lacks effective ways to simulate it.[#item_full_content]

Among the many predictions about the future of artificial intelligence is that models will one day be able to conduct scientific research on their own, leaving humans out of the equation. Already, they can write code, run experiments and search scientific literature, but carrying out open-ended research would require a significant leap in ability.Among the many predictions about the future of artificial intelligence is that models will one day be able to conduct scientific research on their own, leaving humans out of the equation. Already, they can write code, run experiments and search scientific literature, but carrying out open-ended research would require a significant leap in ability.[#item_full_content]

Artificial intelligence is proving to be transformative in its ability to work with language and images. Now, with a growing push to apply AI to scientific discovery, Caltech’s Anima Anandkumar says there is a crucial ingredient missing from most AI models: the ability to understand the physical world. Take, for example, weather models, says Anandkumar, Caltech’s Bren Professor of Computing and Mathematical Sciences. If you want an AI model to predict weather, it must understand chaotic physical systems, like how the atmosphere changes around the planet and over time.Artificial intelligence is proving to be transformative in its ability to work with language and images. Now, with a growing push to apply AI to scientific discovery, Caltech’s Anima Anandkumar says there is a crucial ingredient missing from most AI models: the ability to understand the physical world. Take, for example, weather models, says Anandkumar, Caltech’s Bren Professor of Computing and Mathematical Sciences. If you want an AI model to predict weather, it must understand chaotic physical systems, like how the atmosphere changes around the planet and over time.[#item_full_content]

The trail of likes, shares and downloads we leave across the internet could help predict successful innovations years in advance, Cornell researchers showed by curating two datasets that allowed them to compare early engagement with future impact.The trail of likes, shares and downloads we leave across the internet could help predict successful innovations years in advance, Cornell researchers showed by curating two datasets that allowed them to compare early engagement with future impact.[#item_full_content]