Matrix Math Just Got a Tiny Bit Quicker?

Ever feel like computers are just… slow? We’re constantly pushing them to do more, faster, from rendering the latest games to training those AIs that are writing (or at least inspiring) articles like this one. And at the heart of so many of these tasks lies matrix multiplication – a fundamental operation that’s been the…

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A Sharper Cosmic Map From Template Redshifts

In the vastness of the cosmos, distance isn’t just light-years—it’s the scroll of cosmic history. To chart the three-dimensional map of galaxies, astronomers rely on redshift, a measure of how much the universe has stretched light on its journey to us. Spectroscopic redshifts—where we split light into a spectrum and read off precise fingerprints—are exquisitely…

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Can Gears Teach Robots to Learn From Themselves?

Robotics has long carried two visions at once: a scientist’s dream of learning from data, and an engineer’s wish to respect the stubborn reality of hardware. For humanoid robots, that hardware often looks like a tangle of joints, cables, and belts rather than a clean line from motor to foot. In practice, many learning systems…

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AI Learns to Trust Humans, Gets Way Less Glitchy

Machine learning models are powerful, but they’re often tripped up by complex, real-world data. What if we could teach AI to ask for help? A new study from Liverpool John Moores University proposes an “Augmented Reinforcement Learning” (ARL) framework that does just that: it incorporates human insights into the AI’s decision-making process. Lead researcher Sandesh…

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What a New Map Teaches Us About Infinite Symmetries

The mathematics of symmetry is rarely tidy. It bleeds into physics, geometry, and even the way we model information. In the last decade, a thriving language has emerged to capture these ideas: vertex operator algebras, or VOAs. These objects sit at the crossroads of two-dimensional conformal field theory, string theory, and deep algebraic structures. They’re…

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