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New experimental results simultaneously advance and challenge the theory that the brain’s network of neurons balances on the knife-edge between two phases.
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?
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.
Neural networks are famously incomprehensible, so Been Kim is developing a “translator for humans.”
A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take.
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.
A unique neurological “functional fingerprint” allows scientists to explore the influence of genetics, environment and aging on brain connectivity.
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.
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.