Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work.

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Large language models are powering a new generation of AI agents that could transform computational chemistry from a ...

Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...

Artificial intelligence (AI) safety has turned into a constant cat-and-mouse game. As developers add guardrails to block ...

This new AI acts like a digital scientist, turning messy data into simple rules that explain how the world really works.

Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

In the pharmaceutical discovery process, understanding a drug’s residence time—the duration a molecule remains bound to its ...

This article explores how single-cell multiomics and spatial transcriptomics are illuminating early pregnancy, uncovering ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

The positioning, navigation, and timing (PNT) information is fundamental to modern information systems. Over the years, people have invented many navigation systems to get PNT information, whereas ...