Day 4 of the 5-day Generative AI intensive course by Kaggle and Google covered, among other things, Search Grounding:
With this technique, you can enrich generative AI models with up-to-date and reliable information from the internet — in this case by connecting them to Google Search.
That means the model no longer relies solely on its training data but also integrates information retrieved from search results.
So what's the difference to RAG (Retrieval-Augmented Generation)?
There’s no need to build and manage your own retrieval system (like a vector database), since the additional data is fetched via an API from a search engine.
Here is the link to the corresponding Kaggle notebook: https://www.kaggle.com/code/markishere/day-4-google-search-grounding