Computers

The theoretical side of the field doesn’t require computing machines. But many questions would never have been posed without them.

No one yet knows which technology will power the quantum computers of the future, but the race to create them has already produced some of science’s most intricate machinery.

Today’s computers need safeguards against random energy fluctuations. Thermodynamic computers would put those fluctuations to use.

Fundamental technique lets researchers use a big, expensive “teacher” model to train a “student” model for less.

Reversible programs run backward as easily as they run forward, saving energy in theory. After decades of research, they may soon power AI.

The brain’s astounding cellular diversity and networked complexity could show how to make AI better.

While some fret about technology’s social impacts, Raj Reddy still believes in the power of artificial intelligence to improve lives.

Our computers can get a lot more done when they share the load with other machines.

You don’t need 0s and 1s to perform computations, and in some cases it’s better to avoid them.