Physicists have no clue what’s causing the gallium anomaly, which leaves them in an uncomfortable spot. Are they just missing some error? Or, could it point to a new type of neutrino — one that might also help to explain dark matter? https://lnkd.in/esTY-9Vg
Quanta Magazine
Book and Periodical Publishing
New York, NY 39,649 followers
Big ideas in science and math. Because you want to know more.
About us
Quanta Magazine’s goal is to illuminate basic science and math research through public service journalism. Each article braids the complexities of science with the malleable art of storytelling and is meticulously reported, edited and fact-checked. Launched and funded by the Simons Foundation, Quanta is editorially independent — our articles do not reflect or represent the views of the foundation.
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https://www.quantamagazine.org/
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- Book and Periodical Publishing
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- 11-50 employees
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- New York, NY
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- 2013
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We're #hiring a new Math Staff Writer in New York City Metropolitan Area. Apply today or share this post with your network.
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Paige Madden, who is about to compete in the Olympics for the second time, has been using paddles to measure the force she produces on each stroke. “Our paddles don’t let you lie. We don’t let you fool yourselves,” said Ken Ono, a mathematician who has been working with Madden. https://lnkd.in/eiZN9Hdv
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To see how Earth might fare in the days of a dying sun, astronomers turn to a crystal ball filled with alien planetary systems. Their goal is to study sunlike stars as they balloon into red giants. Tune in to this week’s Quanta Science Podcast. https://lnkd.in/e8FBXjUW
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“It began innocently enough — with Saran Wrap and accelerometers designed for shark tracking,” said Ken Ono, a math professor at UVA and technical consultant to the U.S. Olympic women’s swim team. His mathematical analyses have helped swimmers earn numerous gold medals, which they’re hoping to keep doing when the Paris Olympics kick off on July 26. https://lnkd.in/eiZN9Hdv
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Large language models are built from “deep” neural networks with billions or even trillions of parameters. But even these behemoths, like all machine learning models, are just functions at heart — mathematical shapes. https://lnkd.in/eGUBMPRd
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With efficient algorithms, well-chosen functions and enough examples, machine learning can create powerful computational models that do things we have no idea how to program. https://lnkd.in/eGUBMPRd
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In 1943, before “artificial intelligence” became a buzzword, two researchers proposed a way to teach computers how to learn based on a simple idea: Living organisms learn constantly, so why not take a cue from biology?
How Neural Networks Are Giving Back to Biology
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The mathematician Tibor Radó established the study of exhaustively long computations on Turing machines. He was no stranger to long journeys: Captured during World War I, Radó spent four years in a Siberian prison camp before escaping to Budapest. https://lnkd.in/eqcqZfGv
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Beginning in the spring of 2022, collaborators tackled a stubborn theoretical computer science problem called BB(5). This is the moment when mxdys, an anonymous user on the group’s Discord server, solved the problem using a proof assistant program. https://lnkd.in/eqcqZfGv
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