Materials with advanced customized properties drive innovation in a number of real-life applications across various fields, such as information technology, transportation, green energy and health ...

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

Forbes contributors publish independent expert analyses and insights. We set an example for a better future via education and research. As machine learning progresses at breakneck speed, its ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

A booth demo highlights why the Cognex In-Sight 3800 makes quick work of executing inspection tasks on high-speed ...

Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...

Development of a modern semiconductor requires running many electronic design automation (EDA) tools many times over the course of the project. Every stage, from architectural exploration and design ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

What if the skills you choose to learn today could determine your career trajectory in 2025? The field of machine learning is evolving at a breakneck pace, and with it comes a growing demand for ...