2025-05-10

Retrieval-augmented generation (RAG) promises to help medical AI systems deliver up-to-date and reliable answers. But a new review shows that, so far, RAG rarely works as intended in real-world healthcare settings—and technical, regulatory, and infrastructure hurdles are slowing its adoption.
The article Five major obstacles are holding back RAG systems in healthcare appeared first on
2025-11-04
Enterprise AI has a data problem. Despite billions in investment and increasingly capable language models, most organizations still can't answer basic analytical questions about their document re [...]
2025-10-19
As more companies quickly begin using gen AI, it’s important to avoid a big mistake that could impact its effectiveness: Proper onboarding. Companies spend time and money training new human workers [...]
2025-03-30
Researchers at the Hebrew University of Jerusalem have discovered that the number of documents processed in Retrieval Augmented Generation (RAG) affects language model performance, even when the total [...]
2025-10-29
Enterprise AI agents today face a fundamental timing problem: They can't easily act on critical business events because they aren't always aware of them in real-time.The challenge is infrast [...]
2025-10-24
The next big trend in AI providers appears to be "studio" environments on the web that allow users to spin up agents and AI applications within minutes. Case in point, today the well-funded [...]