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 ...

A new machine learning tool called PhysMAP separates the electrical signatures of different cell types, offering a new way to study schizophrenia and depression.

Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science.

A wildfire forecasting system powered by artificial intelligence was around 30% better at identifying dangerous fire ...

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

Landslide risk is rising as extreme rainfall intensifies. New tools using satellite data and AI can help map where failures ...

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

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

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

Before big tech engineers can improve the fairness of recommendation systems, such as social media feeds and online shopping ...

Scientists have found a way to make AI much better at predicting complex, chaotic systems by tapping into the unique power of ...