Many people are now starting to think about how to bring Gen AI and large language models (LLMs) to production services. You may be wondering "How to integrate LLMs or AI chatbots with existing IT systems, databases and business data?", "We have thousands of products. How can I let LLM memorize them all precisely?", or "How to handle the hallucination issues in AI chatbots to build a reliable service?". Here is a quick solution: grounding with embeddings and vector search.
What is grounding? What are embedding and vector search? In this post, we will learn these crucial concepts to build reliable Gen AI services for enterprise use. But before we dive deeper, here is an example:
This demo is available as a public live demo here. Select "STACKOVERFLOW" and enter any coding question as a query, so it runs a text search on 8 million questions posted on Stack Overflow.