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 ...

From self-driving labs to predictive molecular models, AI is reshaping how chemists discover drugs, design materials, and optimize reactions. By integrating automation, machine learning, and human ...

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

The field of intelligent energy systems has witnessed a remarkable transformation owing to innovations in machine learning. Over the past few decades, the ...

An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center ...

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

What we encounter in LLMs is largely ourselves. A psychoanalytic AI take on transference, countertransference, and the ...

Recently, the global winners of the 2026 Noble Technology Awards have been officially announced. Young data scientist ...

The professionals who work in safety and quality management are accountable for human lives, consumer well-being, and brand ...

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

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

The study offers a valuable resource and integrates multiple complementary datasets to provide insights into regulatory mechanisms, although the conceptual advances are moderate and the central ...