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Anil Ananthaswamy

Contributing Writer

neural networks

Researchers Build AI That Builds AI

By Anil Ananthaswamy
January 25, 2022
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By using hypernetworks, researchers can now preemptively fine-tune artificial neural networks, saving some of the time and expense of training.

Illustration of tangled branches that can also look like the folds in a brain.
neuroscience

To Be Energy-Efficient, Brains Predict Their Perceptions

By Anil Ananthaswamy
November 15, 2021
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Results from neural networks support the idea that brains are “prediction machines” — and that they work that way to conserve energy.

neural networks

A New Link to an Old Model Could Crack the Mystery of Deep Learning

By Anil Ananthaswamy
October 11, 2021
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To help them explain the shocking success of deep neural networks, researchers are turning to older but better-understood models of machine learning.

An illustration showing pink and purple particles flowing around a geometric computer chip.
artificial intelligence

Latest Neural Nets Solve World’s Hardest Equations Faster Than Ever Before

By Anil Ananthaswamy
April 19, 2021
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Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster.

Animation of a neuron that periodically alters its responses to stimuli when it is reset into a new state by another input.
neural networks

Artificial Neural Nets Finally Yield Clues to How Brains Learn

By Anil Ananthaswamy
February 18, 2021
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The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could.

A stylized atom surrounded by concentric shells of increasingly complex organisms.
quantum physics

A New Theorem Maps Out the Limits of Quantum Physics

By Anil Ananthaswamy
December 3, 2020
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The result highlights a fundamental tension: Either the rules of quantum mechanics don’t always apply, or at least one basic assumption about reality must be wrong.

Yarn models of a deep learning network and a brain.
neuroscience

Deep Neural Networks Help to Explain Living Brains

By Anil Ananthaswamy
October 28, 2020
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Deep neural networks, often criticized as “black boxes,” are helping neuroscientists understand the organization of living brains.

quantum information theory

How to Turn a Quantum Computer Into the Ultimate Randomness Generator

By Anil Ananthaswamy
June 19, 2019
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Pure, verifiable randomness is hard to come by. Two proposals show how to make quantum computers into randomness factories.

Art for "New Quantum Paradox Clarifies Where Reality Goes Wrong"
quantum physics

New Quantum Paradox Clarifies Where Our Views of Reality Go Wrong

By Anil Ananthaswamy
December 3, 2018
Read Later

The Frauchiger-Renner thought experiment has shaken up the world of quantum foundations.


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About the author

Anil Ananthaswamy is a journalist and author. He is a 2019-20 MIT Knight Science Journalism fellow. His latest book, Through Two Doors at Once, is about quantum mechanics and the double-slit experiment. He is a former deputy news editor for New Scientist magazine and currently a freelance feature editor for PNAS’s Front Matter. Besides Quanta, he writes for New Scientist, Scientific American, Knowable and Undark, among others. He won the UK Institute of Physics’ Physics Journalism award and the British Association of Science Writers’ award for Best Investigative Journalism. His first book, The Edge of Physics, was voted book of the year in 2010 by Physics World, and his second book, The Man Who Wasn’t There, was long-listed for the 2016 Pen/E. O. Wilson Literary Science Writing Award.

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