Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a ...

Recent advancements in machine learning have significantly impacted the domain of high-speed electronic systems. By leveraging state‐of‐the‐art algorithms and novel network architectures, researchers ...

The growing potential of artificial intelligence (AI) and machine learning (ML) in embedded systems is driving new application solutions and products, but developing AI-based systems can be ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient’s risk of hepatocellular carcinoma (HCC), the most common ...

Electrical power systems engineers need practical methods for predicting solar output power under varying environmental conditions of a single panel. By integrating an Arduino-based real-time data ...

Ashwini Vaishnaw chairs Meity consultative committee on AI, electronics manufacturing, and emerging technologies, ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...

What is a dynamically reconfigurable processor (DRP)? How DRPs accelerate machine-learning applications. Why is the RZ/V2H well-suited for robotic apps? Renesas's RZ/V2H system-on-chip (SoC) is the ...

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...