Key Points
He says the. technological marvels. he is seeing in his field of expertise now is akin to black magic...
I think were at the beginning of a very new sort of paradigm for data where business data, government data, personal data and unstructured data like images, speech, text, etc are all coming together.. The reason he is excited is because of a now widely popular architecture called Retrieval Augmented Generation (RAG), but to understand that we need to first wrap our heads around a concept called AI vectors and..
So, words that mean similar things have vectors that are very close together.. So, you could, Tirthankar says, take a picture of a flower arrangement and feed this into a vector embedding model that will convert that into a list of numbers..
Then the system takes the question vector, and the matching product vectors from the enterprise database and sends all the correspondent documents, which is one giant blob of information, to the large language model...
Tirthankar says that the large language model, which is trained on enormous amounts of data, can then use its general knowledge, and the specialised knowledge that it has retrieved via the RAG architecture, to make an intelligent recommendation...
