Today, businesses face immense pressure to innovate. The rapid evolution of artificial intelligence and data analytics ...

A new trick for modeling molecules with quantum accuracy takes a step toward revealing the equation at the center of a popular simulation approach, which is used in fundamental chemistry and materials ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

The promise of smart test is a data-chain problem before it is an algorithm problem. A device can pass every checkpoint and ...

With the growing emphasis on sustainable development, the demand for environmentally friendly solvents in green chemical ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field. For example, AI-driven adaptive trial designs may ...

“To maximize the likelihood that applications and patents will be found eligible under Section 101 by the USPTO and courts [after Recentive], applicants should carefully craft a narrative of a ...

Researchers in Belgium have discovered that Parkinson’s disease may consist of several hidden subtypes rather than one single disorder. Using artificial intelligence and machine learning, scientists ...

This article examines the work of data scientist Sai Prashanth Pathi in AI for credit risk, focusing on explainable machine learning in regulated finance, governance alignment, fairness, compliance, ...