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 ...

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

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

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

CAMBRIDGE, Mass. and CAMBRIDGE, England, April 21, 2026 /PRNewswire/ -- As AI accelerates across biopharma and other science-driven industries, organizations are encountering a critical bottleneck: ...

Engineers develop a system that captures all the elements of trial and error in material design, enabling reliable ...

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

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

The music industry is in the grip of an intensifying debate over how AI-generated derivatives of existing music should be ...

The tie-up to accelerate AI applications in the financial sector aims to smoothen processes now being done manually. Read ...

For many years, a dominant view in neuroscience was that neurons in the inferotemporal (IT) cortex—a critical center in the ...

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 ...