MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

Knowledge representation is a fundamental aspect of AI, which allows machines to understand, think, and even make choices ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...

Trained on data from NASA's exoplanet-hunting missions, the open-source ExoMiner++ deep learning model uses an advanced ...

Read a story about dogs, and you may remember it the next time you see one bounding through a park. That’s only possible because you have a unified concept of “dog” that isn’t tied to words or images ...