New deep-learning framework reconstructs hourly PM2.5 chemical composition using air-quality and meteorological data ...

A machine-learning loop searched 14 million battery cathode compositions and found fivefold performance gains across four metrics using fewer than 200 experiments.

The world's most critical challenges are accelerating at a rapid pace. The R&D methods tasked with solving them are not—until ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

AI & Society, states that algorithmic systems often construct competing but equally valid “model-worlds,” offering empirical support for a philosophical claim that evidence alone cannot uniquely ...

Organizations racing to harness vast volumes of structured and unstructured data are increasingly turning to Data lakehouse architectures ...

The field of particle physics is approaching a critical horizon defined by challenges including unprecedented data volumes and detector complexity. Upcoming ...

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Today, most investment firms use AI to assist human managers, providing data or suggestions for them to act on. BAILA represents a new category of AI-Managed Investing, where the AI makes the ...

Stanford University is offering an online graduate course Artificial Intelligence: Principles and Techniques to provide students with complete knowledge of curr ...

Class Disrupted is an education podcast featuring author Michael Horn and Futre’s Diane Tavenner in conversation with ...