Multimodal retrieval-augmented generation (RAG) enhances AI retrieval by integrating text, images, and structured data for deeper contextual understanding. A typical multimodal RAG pipeline consists ...

Credit: Image generated by VentureBeat with Gemini 2.5 Flash (nano banana) AI models are only as good as the data they're trained on. That data generally needs to be labeled, curated and organized ...

A new National Science Foundation (NSF) award will support UC Santa Barbara researchers in developing the next generation of cyberinfrastructure for multimodal imaging data. Leading the effort is B. S ...

Data is the holy grail of AI. From nimble startups to global conglomerates, organizations everywhere are pouring billions of dollars to mobilize datasets for highly performant AI applications and ...

The partnership expands BC Platforms' global data partner network and brings access to broad patient populations in India and the United Arab Emirates (UAE). Through the collabora ...

In the early stages of AI adoption, enterprises primarily worked with narrow models trained on single data types—text, images or speech, but rarely all at once. That era is ending. Today’s leading AI ...

PARIS--(BUSINESS WIRE)--Owkin, a pioneer in Agentic AI for decoding the complexities of biology, has launched a comprehensive multimodal patient data discovery program to accelerate multimodal data ...

OneMedNet has announced a strategic partnership with Protege, an AI training data platform, to provide real-time access to multimodal patient data for AI developers and researchers in the healthcare ...

By releasing RealSource, RealMan Robotics aims to break data silos and accelerate global embodied intelligence research. The company plans to continue expanding the dataset, adding scenarios and ...

Researchers have traditionally employed histopathology techniques, which involve the microscopic examination of tissue, to gain insight into disease processes. This approach often leads to subjective ...