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computer science

Diagram showing show the hierarchy of different classes.
Abstractions blog

A Short Guide to Hard Problems

What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape.

Illustration for "Finally, A Problem That Only Quantum Computers Will Ever Be Able to Solve"
computational complexity

Finally, a Problem That Only Quantum Computers Will Ever Be Able to Solve

Computer scientists have been searching for years for a type of problem that a quantum computer can solve but that any possible future classical computer cannot. Now they’ve found one.

Art for "A Classical Math Problem Gets Pulled Into the Modern World"
algorithms

A Classical Math Problem Gets Pulled Into the Modern World

A century ago, the great mathematician David Hilbert posed a probing question in pure mathematics. A recent advance in optimization theory is bringing Hilbert’s work into a world of self-driving cars.

Photo of Judea Pearl
Q&A

To Build Truly Intelligent Machines, Teach Them Cause and Effect

Judea Pearl, a pioneering figure in artificial intelligence, argues that AI has been stuck in a decades-long rut. His prescription for progress? Teach machines to understand the question why.

Art for "Artificial Neural Nets Grow Brainlike Navigation Cells"
Abstractions blog

Artificial Neural Nets Grow Brainlike Navigation Cells

Faced with a navigational challenge, neural networks spontaneously evolved units resembling the grid cells that help living animals find their way.

Lede art for "First Big Steps Toward Proving the Unique Games Conjecture"
computational complexity

First Big Steps Toward Proving the Unique Games Conjecture

The latest in a new series of proofs brings theoretical computer scientists within striking distance of one of the great conjectures of their discipline.

Gif illustration for "Machine Learning’s ‘Amazing’ Ability to Predict Chaos"
chaos theory

Machine Learning’s ‘Amazing’ Ability to Predict Chaos

In new computer experiments, artificial-intelligence algorithms can tell the future of chaotic systems.

520px photo of Barbara Engelhardt
Q&A

A Statistical Search for Genomic Truths

The computer scientist Barbara Engelhardt develops machine-learning models and methods to scour human genomes for the elusive causes and mechanisms of disease.

Lede art for "Why Self-Taught Artificial Intelligence Has Trouble With the Real World"
artificial intelligence

Why Self-Taught Artificial Intelligence Has Trouble With the Real World

The latest artificial intelligence systems start from zero knowledge of a game and grow to world-beating in a matter of hours. But researchers are struggling to apply these systems beyond the arcade.