It's no secret that ChatGPT, the artificial intelligence chatbot from OpenAI, has taken the world by storm and is reinventing how most of us complete everyday tasks. Now that OpenAI has open-sourced retrieval plugins for ChatGPT, allowing anyone to develop their own knowledge base retrieval app, expect to see an explosion of solutions helping people access information at lightning speed.
At the core of these chat solutions, data models transform unstructured data into vector embeddings stored in a vector database. With these embeddings, developers can perform similarity searches to provide the most relevant answers to their users. Join Frank Liu, ML architect at Zilliz, for a session on why vector databases are critical to the success of these LLM-based chat solutions.
In this session, you'll learn:
- What is a vector database
- Why it is important to store your embeddings in a purpose-built database
- Why dumping your embeddings into Postgres is a bad idea
- How we built a chat knowledge base for open-source projects using Zilliz, prompts-as-code, and ChatGPT
Don't miss this live event on Wednesday, April 26 - 11:00 am PT / 2:00 pm ET.
Register now to attend Vector Databases Have Entered the Chat – How ChatGPT Is Fueling the Need for Specialized Vector Storage.