Can an Open-Source Engine Teach AI to Learn Faster?

Data pours into perception systems the way rain floods a city street: streams from cameras, sensors, and roadside networks, more than any single team can neatly label. The challenge isn’t just volume; it’s bias. The most interesting moments in traffic aren’t the everyday ones that appear in textbooks, but the rare, strange, or dangerous events—the…

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Anomaly Maps Guide AI to Find Prostate Cancer

In MRI suites around the world, radiologists parse intricate textures and shapes, hunting for the telltale signs of clinically significant prostate cancer. It’s a careful craft, a blend of pattern recognition and medical intuition, and it can be slow—especially when clinicians must comb through thousands of slices to segment the exact tumor boundaries. A new…

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Robots’ Looks: A New Way to Measure What Matters

The Robot Morphology Revolution Forget broad strokes like “humanoid” or “animal-like.” A groundbreaking new framework from the University of Bremen, called METAMORPH, is poised to revolutionize how we understand and classify robot appearance. Led by researchers Rachel Ringe, Robin Nolte, Nima Zargham, Robert Porzel, and Rainer Malaka, this approach moves beyond simple categories to a…

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TeV Halos May Be Common Around Middle-Aged Pulsars

Pulsars are the embers of exploded stars: dense, fast, and still wonderfully restless. They spin hundreds of times per second, carving out a wind of charged particles that travel through the surrounding space and, in some cases, light up the sky in gamma rays at energies that dwarf visible light. For years astronomers watched a…

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AI Teaches Itself to Watch—and Decode—Reality

Imagine trying to teach a computer to understand video the way a human does. It’s not just about recognizing objects; it’s about understanding the flow of time, the sequence of events, and the subtle cues that tell us what’s important. Now, a team at Nanyang Technological University and ByteDance Inc. is pushing the boundaries of…

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