Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...

Humans have struggled to make truly intelligent machines. Maybe we need to let them get on with it themselves. A little stick figure with a wedge-shaped head shuffles across the screen. It moves in a ...

What happens when companies on digital labor platforms no longer decide for themselves how much to pay their workers, but ...

Researchers have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome.

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...

In the animal kingdom, energy conservation is essential for survival. That's why our brains have evolved to be extremely ...

A body of healthcare AI research connects data infrastructure, machine learning, and natural language processing across medical applications. The studies examine automated data collection, cancer ...