What's up in
After successfully predicting laboratory earthquakes, a team of geophysicists has applied a machine learning algorithm to quakes in the Pacific Northwest.
In some ways, machine vision is superior to human vision. In other ways, it may never catch up.
Iyad Rahwan’s radical idea: The best way to understand algorithms is to observe their behavior in the wild.
The “sensitivity” conjecture stumped many top computer scientists, yet the new proof is so simple that one researcher summed it up in a single tweet.
The computer vision scientist Greg Johnson is building systems that can recognize organelles on sight and show the dynamics of living cells more clearly than microscopy can.
Researchers are getting close to building a quantum computer that can perform tasks a classical computer can’t. Here’s what the milestone will mean.
Consciousness is a famously hard problem, so Hod Lipson is starting from the basics: with self-aware robots that can help us understand how we think.
To researchers’ surprise, deep learning vision algorithms often fail at classifying images because they mostly take cues from textures, not shapes.
Pure, verifiable randomness is hard to come by. Two proposals show how to make quantum computers into randomness factories.