Are you navigating the complex world of vector databases in Postgres? Explore PGVector and its indexes: Flat, HNSW, and IVFFlat. Dive into the nuances of accuracy, speed, and scalability to make informed decisions.
Discovered by the sudden hype around retrieval-augmented generation (RAG), vector databases quickly gained traction. The article provides a guiding hand for navigating this new landscape.
Exploring Hypothetical Questions and HyDE strategies, designed to boost the accuracy of LLM-based applications by refining the match between user queries and data. It examines the generation of hypothetical questions and answers emphasizing the contrast in their approach.
Looking into the scalability problem of the RAG, the article explores the idea of Hierarchical Index Retrieval. A retrieval strategy that aims to deal with the problem through progressive narrowing of the search space.
Continuing on the RAG strategies series, the article explores how to use the chunk size to improve the retrieval process performance. It presents two popular strategies: Sentence Window Retrieval and Auto-Merging Retrieval.
Delving into the essentials of Retrieval-Augmented Generation (RAG) and Basic Index Retrieval, showcasing how they complement Language Large Models by enriching them with targeted, domain-specific knowledge for more nuanced, human-like responses.
Exploring the fusion of large language models with external data retrieval to transform AI applications. The series offers a deep dive into practical strategies and insights for implementing this innovative approach.
Short intro to the custom clock process on Heroku for greater control and scheduling visibility.
What can QA Engineer do to feel like a part of a team, and not as if they are working against everyone else when reporting issues?
It seems like only yesterday that Pixion was founded with a clear goal in mind — create a small company which only has the best of the best, and is able to overcome any obstacle.
