yarp: yet another rag post (this time using sql)

you don’t have to know python or bother your data scientists to start exploring genai concepts like rag; you just need a tool that offers these features in a familiar sql interface

unstructured docs in ai (the wild west)

rag ai apps can only be as good as the parsed and chunked data that fuels them – testing, testing, and more testing the outputs of all the various available libraries with the front-end apps is critical

the effect of ai on intelligence (behold the idiocracy)

the long-term benefits of sunscreen have been proved by scientists whereas my advice on ai has no basis more reliable than my own meandering experience; i will dispense this advice now, but trust me on the sunscreen

understanding rag ai apps (and the pipelines that feed them)

i’m learning all about rag ai apps and wanted to try to explain, at a high-level, what these are all about plus do the same for the etl pipelines that are key to their success

finally checking out chatgpt (adding a new tool in my toolbelt)

putting aside my (natural?) fear of artificial intelligence, i finally got around to exploring (testing?) chatgpt that everyone has been talking about for many months now