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 ...

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 ...

A model made using machine learning can predict if CPAP use in patients with obstructive sleep apnea will benefit or harm ...

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...

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

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 ...

Most public talk about AI focuses on large language models and flashy generative tools. But honestly, the most dependable ...

The impact of AI systems cannot always be attributed to epistemic or ethical failures. Much of their impact can appear initially ethically neutral in the absence of obvious harm. A separate set of ...

Three new books warn against turning into the person the algorithm thinks you are. Like a lot of Netflix subscribers, I find that my personal feed tends to be hit or miss. Usually more miss. The ...