Earth observation relies on diverse imaging systems whose varying spatial, spectral, radiometric, and temporal ...

A difficulty-graded mouse brain dataset pairs 3D microscopy images with verified neuron reconstructions to support AI-driven ...

Developers are increasingly relying on large language models (LLMs) for everyday computing tasks such as fixing bugs, ...

AWS recently announced Amazon S3 Annotations, a feature that lets teams attach rich, searchable context such as summaries, ...

Abstract: Federated Semi-Supervised Learning (FSSL) aims to learn a global model from different clients in an environment with both labeled and unlabeled data. Most of the existing FSSL work generally ...

A new study combines Large Language Models and behavioral mathematics to analyze human decision-making text data at scale.

Today, frontier AI labs such as OpenAI and Anthropic are among its biggest and most strategically important customers. These companies need vast amounts of data to train foundation models. But that is ...

Structural biology has long been a leader in open data culture; the Protein Data Bank (PDB), Electron Microscopy Data Bank (EMDB), and Biological Magnetic ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Every AI model depends on labeled data. Data annotation is the process of tagging images, text, audio, or video so that ...