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 ...

Most contemporary artificial intelligence (AI) systems learn to complete tasks via machine learning and deep learning. Machine learning is a computational approach that allows models to uncover ...

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 ...

Enterprise AI workloads require infrastructure designed for large-scale data processing and distributed computing.

Machine Learning (ML) and Artificial Intelligence (AI) have become essential technologies across industries, automating tasks at a speed and scale far beyond human capabilities. However, building ...

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 ...

Researchers from Google DeepMind in Berlin, BIFOLD, and the Technical University of Berlin have introduced a new machine ...

Machine learning systems increasingly underpin modern technological innovation, and their effectiveness is inextricably linked to advanced data management solutions. Contemporary research has placed a ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Compare Data Scientist vs Machine Learning Engineer roles in India 2026. Explore salary, skills, career paths, and find which ...

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 ...