Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

Muons are a key subatomic particle in the discovery of new physics, but after particle collision, they’re difficult to track.

Mr. Ingram’s startup, Lodebar, feeds high-frequency market data into a machine-learning algorithm that turns it into jazz.

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 ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

For centuries, humans looked to seers and astrologers to determine fate. Today, we look to algorithms, and the loss of agency is the same.

Intelligent organizations prioritize investments in machine learning and real-time data to improve decision making, accelerate revenue generation efforts, reduce operational expenses and protect ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...

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 ...