rag

With big data comes big responsibility – of making it FAIR: Findable, Accessible, Interoperable and Reusable. But ensuring data is truly FAIR is challenging as scaling search systems to handle big data requires significant computational resources. Let’s take an example from a user’s perspective. Say you are using BioStudies, our general purpose repository for publishing life sciences data, and want to download data from all functional genomics studies on chickens this year that use the sequencing assay technology....

How do you explain Retrieval Augmented Generation (RAG) and agents to a 10 year old? I had to do it last week. It started when I asked them if they knew how AI works. “AI, like ChatGPT? You type a question in and it searches for the answer” “Yes, but not all AIs have access to the Internet so sometimes the answer is not correct. Let me give you an example....