RECENT ARTICLES

BYLINES: QUANTA, SCIENTIFIC AMERICAN, NATURE, NEW SCIENTIST …

TOPICS: AI, machine learning, computational neuroscience, quantum physics, cosmology …

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NATURE / ARTIFICIAL INTELLIGENCE

How close is AI to human-level intelligence?

Large language models such as OpenAI’s o1 have electrified the debate over achieving artificial general intelligence, or AGI. But they are unlikely to reach this milestone on their own.

QUANTA MAGAZINE / QUANTUM PHYSICS

In the Quantum World, Even Points of View Are Uncertain

The reference frames from which observers view quantum events can themselves have multiple possible locations at once — an insight with potentially major ramifications.

MIT TECHNOLOGY REVIEW/ MACHINE LEARNING

A new way to build neural networks could make AI more understandable

The simplified approach makes it easier to see how neural networks produce the outputs they do.

NAUTILUS MAGAZINE / MACHINE LEARNING

The Elegant Math of Machine Learning

Anil Ananthaswamy’s 3 greatest revelations while writing Why Machines Learn.

BIG THINK / ARTIFICIAL INTELLIGENCE

10 profound answers about the math behind AI

It’s knowledgeable, confident, and behaves human-like in many ways. But it’s not magic that powers AI though; it’s just math and data.

SCIENTIFIC AMERICAN / QUANTUM PHYSICS

Could AI Save Schroedinger's Cat?

Outcomes in quantum mechanics depend on observations. But must the observer be human?

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jpgfactory/Getty Images

SCIENTIFIC AMERICAN / COSMOLOGY

Collapsing Sheets of Spacetime Could Explain Dark Matter and Why the Universe ‘Hums’

Domain walls, long a divisive topic in physics, may be ideal explanations for some bizarre cosmic quirks

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QUANTA / MACHINE LEARNING

How Do Machines ‘Grok’ Data?

By apparently overtraining them, researchers have seen neural networks discover novel solutions to problems.

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Quanta Magazine

QUANTA / MACHINE LEARNING

New Theory Suggests Chatbots Can Understand Text

Far from being “stochastic parrots,” the biggest large language models seem to learn enough skills to understand the words they’re processing.

IMAGE: Myriam Wares for
Quanta Magazine

QUANTA / HIGH-DIMENSIONAL COMPUTING

A New Approach to Computation Reimagines Artificial Intelligence

By imbuing enormous vectors with semantic meaning, we can get machines to reason more abstractly — and efficiently — than before

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NEW SCIENTIST / BOOK REVIEW

Is Maths Real? review: Getting comfortable not knowing the answers

Eugenia Cheng's latest book about mathematics asks deceptively simple questions that hint at the deep mysteries beneath

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NATURE / ESSAY, QUANTUM PHYSICS

Particle, wave, both or neither? The experiment that challenges all we know about reality

Thomas Young’s double-slit experiment originally served to prove that light is a wave — but later quantum versions have made for a much fuzzier picture.

Illustration by Fabio Buonocore

NATURE / FEATURE, LARGE LANGUAGE MODELS

In AI, is bigger always better?

As generative AI models grow larger and more powerful, some scientists advocate for leaner, more energy-efficient systems.

Samuel Velasco/Quanta Magazine; source: Shutterstock

QUANTA / MACHINE LEARNING

The Physics Principle That Inspired Modern AI Art

Diffusion models generate incredible images by learning to reverse the process that, among other things, causes ink to spread through water.

Image: Señor Salme for Quanta Magazine

QUANTA / MACHINE LEARNING

Self-Taught AI Shows Similarities to How the Brain Works

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful.

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QUANTA / MACHINE LEARNING

Researchers Build AI That Builds AI

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

IMAGE: Olivia Fields for Quanta Magazine

QUANTA / COMPUTATIONAL NEUROSCIENCE

To Be Energy-Efficient, Brains Predict Their Perceptions

Results from neural networks support the idea that brains are “prediction machines” — and that they work that way to conserve energy.

IMAGE: Olena Shmahalo/Quanta Magazine

QUANTA / DEEP LEARNING

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

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

DVDP for Quanta Magazine

QUANTA / COMPUTATIONAL NEUROSCIENCE

Artificial Neural Nets Finally Yield Clues to How Brains Learn

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.

Corinne Reid for Quanta Magazine

QUANTA / QUANTUM FOUNDATIONS

A New Theorem Maps Out the Limits of Quantum Physics

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.

Hiné Mizushima for Quanta Magazine

QUANTA / COMPUTATIONAL NEUROSCIENCE

Deep Neural Networks Help to Explain Living Brains

Deep neural networks, often criticized as “black boxes,” are helping neuroscientists understand the organization of living brains.

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Scientific American
Quanta Magazine
New Scientist
Nature
Knowable Magazine
Nautilus
MIT Technology Review
Discover Magazine
Aeon Magazine