Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines. By Daniel Fusch Neel Somani, a ...

CorVista Health, a leader in noninvasive cardiovascular diagnostics, today announced new data evaluating a physiologic signal–based machine-learning model for detecting cardiac ischemia. The data was ...

In recent years, the intersection of artificial intelligence (AI), machine learning (ML), and acoustic signal processing has emerged as a rapidly advancing field, offering new ways to analyze, ...

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...

Researchers at Tohoku University and Future University Hakodate have trained cultured rat cortical neurons to perform ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...