Edge AI Learns to Sense and Decide in Real Time

In a world racing toward smarter devices, the challenge isn’t just collecting data but turning it into quick, trustworthy decisions where they matter most. Imagine autonomous vehicles, delivery drones, or factory robots that must both feel their surroundings and decide what to do in the blink of an eye. A new study from a team…

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AI’s New Trick: Rewriting Its Own Mind Without Retraining

Imagine a world where we could fine-tune artificial intelligence without the usual massive computational costs and risks. That’s the promise of a groundbreaking new technique developed by researchers at UNC Chapel Hill, detailed in their paper, GRAINS (Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs). Forget painstaking retraining; this method allows us to tweak…

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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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The Quiet Power of First Segments in Long Documents

The challenge of finding a needle in a digital haystack grows bigger when the haystack is a book-length document. Traditional search engines stumble as documents swell beyond a few screens, forcing compromises between speed and accuracy. In information retrieval, researchers have tried to teach machines to skim and weigh words the way we do, but…

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A Dictionary Keeps Transformers Lean and Smart

A Dictionary Keeps Transformers Lean and Smart Why do today’s AI models feel like carbon-heavy beasts even when they’re solving elegant problems? Because the brains behind them—transformers—are built by stacking repeating blocks that each carry a mountain of numbers. In large language models, the attention mechanism is the star, connecting every token to every other…

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When Math Mirrors Itself: A Banach Space’s Hidden Symmetry

Imagine a perfectly balanced scale, where each side represents a different aspect of a mathematical structure. This analogy, while imperfect, helps capture the essence of Sudeshna Basu’s groundbreaking work on Banach spaces, a field of mathematics dealing with abstract vector spaces. Basu’s research, conducted while visiting the National Institute of Science Education and Research Bhubaneshwar,…

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