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How Artificial Intelligence Is Changing Science
The latest AI algorithms are probing the evolution of galaxies, calculating quantum wave functions, discovering new chemical compounds and more. Is there anything that scientists do that can’t be automated?
Foundations Built for a General Theory of Neural Networks
Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural network’s form will influence its function.
A New Approach to Understanding How Machines Think
Neural networks are famously incomprehensible, so Been Kim is developing a “translator for humans.”
Machine Learning Confronts the Elephant in the Room
A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take.
New AI Strategy Mimics How Brains Learn to Smell
Machine learning techniques are commonly based on how the visual system processes information. To beat their limitations, scientists are drawing inspiration from the sense of smell.
‘Functional Fingerprint’ May Identify Brains Over a Lifetime
A unique neurological “functional fingerprint” allows scientists to explore the influence of genetics, environment and aging on brain connectivity.
A Math Theory for Why People Hallucinate
Psychedelic drugs can trigger characteristic hallucinations, which have long been thought to hold clues about the brain’s circuitry. After nearly a century of study, a possible explanation is crystallizing.
Brains May Teeter Near Their Tipping Point
In a renewed attempt at a grand unified theory of brain function, physicists now argue that brains optimize performance by staying near — though not exactly at — the critical point between two phases.
Machine Learning’s ‘Amazing’ Ability to Predict Chaos
In new computer experiments, artificial-intelligence algorithms can tell the future of chaotic systems.