Paper Review: Vector Search with OpenAI Embeddings

In this video, I discuss a recent paper titled "Vector Search with OpenAI Embeddings" published by the University of Waterloo. The paper presents a straightforward approach to solving the information retrieval problem, where the goal is to identify relevant documents in a large data store based on a given query. The authors argue that by using OpenAI embeddings with a traditional data store like Lucene, there is no need for complex vector storage systems. They also highlight the engineering effort required and evaluate their approach on the MS-Marco dataset. Overall, this paper demonstrates that effective information retrieval can be achieved using off-the-shelf models and databases. Arxiv link: https://arxiv.org/pdf/2308.14963.pdf