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Feedback First: Accelerating AI Development with Early Insights

Feedback First: Accelerating AI Development with Early Insights

Explore the pivotal role of early user feedback in refining and directing the development of generative AI applications.

Jerzy Czopek
In the rapidly evolving landscape of generative AI, developing applications based on Large Language Models (LLMs) presents a unique set of challenges and opportunities. As I have recently learned, one of the most critical steps in this journey is actively seeking out and using early user feedback. In this blog post, I will explain why it’s so crucial to listen to users right from the start. Gaining Insights into User Interaction When building LLM-based applications, understanding how users interact with your tool is crucial.
Deploy Azure PostgreSQL flexible server with pgvector extension

Deploy Azure PostgreSQL flexible server with pgvector extension

Easy steps to deploy Azure PostgreSQL flexible server with pgvector extension for vector similarity search.

Jerzy Czopek
Using vector storage and search is becoming increasingly popular due to the momentum that Generative AI has gained. It is a critical part of many use cases that require relevant context for prompts, while staying within the token limit of LLMs. There are many options available for storing vector data and performing searches. Some are provided as third-party hosted APIs, while others can be deployed as containers to Kubernetes clusters. There is also an interesting alternative: using a good old PostgreSQL database with the pgvector extension!