Enterprises seeking to harness the power of Large Language Models (LLMs) have faced a challenging dilemma – entrusting their data to third-party services or building an in-house machine learning team. The game is changing with the groundbreaking partnership between Mano AI and Giga ML.

Outlining the risks and challenges associated with deploying large language models (LLMs) in large enterprises, such as data privacy violations and data leakage. We provide solutions for mitigating these risks, including deploying local LLM services, leveraging org wide data aggregation, and implementing differential privacy techniques.

Let's explore the most popular vector databases based on scalability, performance, flexibility, ease of use, and reliability. The databases discussed include Milvus, Pinecone, Qdrant, Chroma, and PGVector.