Is this large enough to be a privacy LLM?

https://fpf.org/blog/the-privaseer-project-in-2023-access-to-1-4-million-privacy-policies-in-one-searchable-body-of-documents/

THE PRIVASEER PROJECT IN 2023: ACCESS TO 1.4 MILLION PRIVACY POLICIES IN ONE SEARCHABLE BODY OF DOCUMENTS

In the summer of 2021, FPF announced our participation in a collaborative project with researchers from the Pennsylvania State University and the University of Michigan to develop and build a searchable database of privacy policies and other privacy-related documents, with the support of the National Science Foundation. This project, PrivaSeer, has since become an evolving, publicly available search engine of more than 1.4 million privacy policies.

New term, new tool. (Watch the video!)

https://research.ibm.com/blog/retrieval-augmented-generation-RAG

What is retrieval-augmented generation?

RAG is an AI framework for retrieving facts from an external knowledge base to ground large language models (LLMs) on the most accurate, up-to-date information and to give users insight into LLMs' generative process.

Perspective.

https://www.niemanlab.org/2023/12/ai-changes-everything-and-nothing/

AI changes everything…and nothing

… As I have begun talking about AI over the past several months — in classes, at conferences, and in conversation with friends and colleagues — I keep repeating that we are going to look back at the past couple decades of search as the dark ages of information. “Remember when we had to Google stuff and then go to websites and read them and hope they had the answers to our questions?” Google’s algorithm that now gives us excellent-quality search results will feel as antiquated as a MySpace Top 8 when we are able to have a conversation with a bot that seemingly knows everything. These all-knowing platforms are now being referred to as “artificial general intelligence.”