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 ...

To generate usable data, NSWCPD engineers built a controlled test environment and introduced faults such as air leaks, inlet ...

Discovering and characterizing new materials is important for unlocking advances in fields like clean energy, advanced ...

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

Engineers at NIMS Develop a System That Captures All the Elements of Trial and Error in Material Design, Enabling Reliable ...

By Kenrick Cai LAS VEGAS, April 22 (Reuters) - Alphabet is deepening a push into enterprise software, signaling to investors ...

Explore how AI frameworks are reshaping enterprise innovation in 2026, enabling scalable solutions, faster decision-making, ...

Target identification is the first and perhaps most critical step in drug discovery and development. Although the human genome contains roughly 20,000 protein-coding genes, only about 4,500 are ...

GBH Morning Edition host Mark Herz spoke with MIT computer science professor Marzyeh Ghassemi about AI's use in medicine.

Neuroscientist Vivienne Ming argues in her new book that the biggest risk of artificial intelligence is people using it too ...

Mira Murati's Thinking Machines Lab has signed a multi-billion-dollar deal with Google Cloud for AI infrastructure powered by ...

As Anthropic’s Mythos signals a shift to unprecedented machine-speed vulnerability discovery, EPSS is gaining renewed ...