Tag: similarity search
Querying Vectors And Things That Can Go Wrong With Them
Couchbase 7.6 introduces Vector Search into the Couchbase architecture, expanding its search capabilities by leaps and bounds. This article showcases how this affects search queries, how we have to adapt in certain situations and how to efficiently use this latest...
Vector Search Performance: The Rise of Recall
Introducing vector search (KNN), with its distance-based similarity scoring, into the existing Search paradigm necessitated a shift in how we thought about “relevant” results and how to measure them. Text based indexes use tf-idf as their scoring mechanism with the...
What are Foundation Models? (Plus Types and Use Cases)
What is a Foundation Model? A foundation model is a powerful type of artificial intelligence (AI) trained on massive amounts of general data, allowing it to tackle a broad range of tasks. Foundation models, such as OpenAI’s GPT (Generative Pre-trained...
What is Vector Similarity Search?
Vector Similarity Search Overview Vector similarity search is a technique that finds similar content or data according to their vector representations. Imagine each piece of data as a collection of numbers arranged in a specific way. By comparing these collections...