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Back to the future: Is light-speed analog computing on the horizon?

Scientists have achieved a breakthrough in analog computing, developing a programmable electronic circuit that harnesses the properties of high-frequency electromagnetic waves to perform complex parallel processing at light-speed.

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Novel AI tool opens 3D modeling to blind and low-vision programmers

Blind and low-vision programmers have long been locked out of three-dimensional modeling software, which depends on sighted users dragging, rotating and inspecting shapes on screen.

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AI model can manipulate time to make better predictions in a wide range of fields

In the world around us, many things exist in the context of time: a bird's path through the sky is understood as different positions over a period of time, and conversations as a series of words occurring one after another.

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Cracking a long-standing weakness in a classic algorithm for programming reconfigurable chips

Researchers from EPFL, AMD, and the University of Novi Sad have uncovered a long-standing inefficiency in the algorithm that programs millions of reconfigurable chips used worldwide, a discovery that could reshape how future generations of these are designed and programmed.

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New design tackles integer factorization problems through digital probabilistic computing

Probabilistic Ising machines (PIMs) are advanced and specialized computing systems that could tackle computationally hard problems, such as optimization or integer factorization tasks, more efficiently than classical systems. To solve problems, PIMs rely on interacting probabilistic bits (p-bits), networks of interacting units of digital information with values that randomly fluctuate between 0 and 1, but that can be biased to converge to yield desired solutions.

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How to ensure high-quality synthetic wireless data when real-world data runs dry

To train artificial intelligence (AI) models, researchers need good data and lots of it. However, most real-world data has already been used, leading scientists to generate synthetic data. While the generated data helps solve the issue of quantity, it may not always have good quality, and assessing its quality has been overlooked.

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Fast traffic algorithm could improve real-time traffic forecasts

Everyone hates traffic. Big cities in particular are plagued by an overabundance of vehicles, turning a simple crosstown jaunt into an odyssey during rush hour. Part of the problem is that traffic is incredibly complex, and a small change in one part of the system can have ripple effects that alter traffic patterns throughout a city. City planners attempting to improve local traffic grids can often struggle to foresee all the effects their changes could have.

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AI scaling laws: Universal guide estimates how LLMs will perform based on smaller models in same family

When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model.

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Robotic assembly lines gain flexibility as algorithm plans tasks, teams and floor layouts

Developments in autonomous robotics have the potential to revolutionize manufacturing processes, making them more flexible, customizable, and efficient. But coordinating fleets of autonomous, mobile robots in a shared space—and helping them work with each other and with human partners—is an extremely complicated task.

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The AI model that teaches itself to think through problems, no humans required

Artificial intelligence is getting smarter every day, but it still has its limits. One of the biggest challenges has been teaching advanced AI models to reason, which means solving problems step by step. But in a new paper published in the journal Nature, the team from DeepSeek AI, a Chinese artificial intelligence company, reports that they were able to teach their R1 model to reason on its own without human input.

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Rethinking train delays with quantum power

Train delays can cascade into stalled commutes, economic losses, and vacation snags. Scheduling trains is computationally complex, though: It can take hours or days to solve large transportation networks on traditional computers, when disruptions like train breakdowns or traffic accidents demand much quicker solutions.

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Hidden insights in GPS data can track lane changes and improve AV safety, study shows

Understanding how and when drivers change lanes is key to improving highway traffic flow, safety and autonomous vehicle performance, and a new approach developed at the University of Michigan outperforms current methods using only GPS data.

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What the crash of a play-to-earn crypto game reveals about the future of Web3

At the height of the COVID-19 pandemic, players flocked to Axie Infinity, a blockchain-based video game where users received cryptocurrency tokens for their time spent playing. In 2022, when the broader crypto market crashed and a massive hack erased players' earnings, most users fled. A new study by Cornell researchers has investigated why some players stuck around.

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Motion-compensation approach delivers sharper single-pixel imaging for dynamic scenes

Researchers have developed a motion-compensation method that allows single-pixel imaging to capture sharp images of complex dynamic scenes. The new approach could expand the practical utility of this computational imaging method by enabling clearer images of moving targets and improving the quality of surveillance images.

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New technology turns paintings into holograms, bringing art to life

Artists are always looking for new ways to create and express themselves. A growing trend is the use of multiple layers of see-through materials, such as Plexiglas, to create paintings that have real depth, transforming two-dimensional images into three-dimensional illusions that feel more realistic and lifelike. But can these layered works be made even more immersive?

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