Large language models (like ChatGPT) have billions of trainable parameters. LoRA locks pre-trained weights and fine-tunes model output based on a much smaller number of more relevant parameters.
Unlike traditional databases that store and retrieve data using exact match queries, vector databases allow for similarity searches based on mathematical distance between vectors.
