What Are Vector Databases

The video discusses the rise of vector databases, highlighting recent funding rounds and humorous anecdotes about launching a new database. It explains vectors and embeddings, their applications in AI, and how vector databases differ from other types. A coding demonstration using Chroma and JavaScript is provided, showing how to work with vector databases. The video also explores how vector databases extend LLMs with long memory and integrate with tools like Lang Chain. Finally, it touches on AI trends, AGI, and the potential impact on engineering roles.

What is a vector in the context of vector databases?

• A text document

• A single number

• A database table

• An array of numbers

How do vector databases differ from relational databases?

• They cluster arrays of numbers based on similarity

• They do not support complex queries

• They use rows and columns

• They store data in documents

Which of the following is NOT a vector database mentioned in the video?

• We V8

• Pine Cone

• Chroma

• MongoDB

What is one of the main benefits of using vector databases with language models?

• They increase the speed of training

• They simplify the model architecture

• They provide long-term memory

• They reduce the size of the model

What is a current trend in AI development mentioned in the video?

• Creating artificial general intelligence

• Developing only open-source tools

• Focusing on small-scale models

• Eliminating the use of vector databases