Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper publishing April 22 in the Cell Press ...

Newly published research from a leading computer scientist warns that the use of generative AI to design, train, or perform ...

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

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 ...

Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...

The rapid acceleration of AI adoption across industries is reshaping not only products, but also the engineering roles that support them. As organizations move machine learning systems from ...

Engineers at NIMS Develop a System That Captures All the Elements of Trial and Error in Material Design, Enabling Reliable Reproduction of the Reasoning Processes and Results TSUKUBA, JAPAN - April 22 ...

I’ve been flying multispectral missions for a few years now, and the biggest surprise of these systems is how much processing ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...