Check out the blogs that falls under the category Vector Search. Learn more about the vector search best practices – interacting with AI LLMs and more
Category: Vector Search
Accelerate Couchbase-Powered RAG AI Application With NVIDIA NIM/NeMo and LangChain
Today, we’re excited to announce our new integration with NVIDIA NIM/NeMo. In this blog post, we present a solution concept of an interactive chatbot based on a Retrieval Augmented Generation (RAG) architecture with Couchbase Capella as a Vector database. The retrieval...
Enhancing GenAI for Privacy and Performance: The Future of Personalized AI with Edge Vector Databases
The evolution of Generative AI (GenAI) is marked by a significant transition from model development to application development. As these AI models mature, the focus shifts to integrating them into real-world applications, bringing about new challenges. Application developers and infrastructure...
Develop Performant RAG Apps With Couchbase and Vectorize
For technology leaders and developers, the process of integrating rich, proprietary data into generative AI applications is often filled with challenges. Vector similarity search and retrieval augmented generation are powerful tools to help with this, but one mistake extracting, chunking,...
How Adaptive Applications Unlock Innovation in a New AI Age
We stand on the verge of a generative AI (GenAI) revolution. Some 98% of organizations have specific GenAI goals for 2024 — accounting for nearly a third of digital modernization spend last year and in 2024, according to new research...
Couchbase Capella™ Wins Two Awards in the 2024 Stevie American Business Awards
As the cloud database market continues to evolve, Couchbase is committed to providing unmatched versatility, performance, and scalability to empower customers and partners to be at the forefront of innovation. As a testament to Couchbase’s continued advancements, we’re thrilled to...
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...
Hybrid Search: An Overview
What Is Hybrid Search? Hybrid search typically refers to a search approach that combines multiple search methodologies or technologies to provide more comprehensive and accurate results. In the context of information retrieval, hybrid search often involves blending traditional keyword-based searching...
Building Real-world AI Applications at the Beeloud and Build 2024 AI Hackathon
Couchbase recently sponsored the Beeloud and Build 2024 AI Hackathon. BeeLoud’s (the event’s organizer) goal was to put the Vancouver tech scene on the map and explore the AI world alongside impactful and high-profile builders, mentors, and investor judges. Beeloud...
Twitter Thread tl;dr With AI? Part 2
In part 1 we saw how to scrape Twitter, turn tweets in JSON documents, get an embedding representation of that tweet, store everything in Couchbase and how to run a vector search. These are the first steps of a Retrieval...
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...
Twitter Thread tl;dr With AI? Part 1
Because who has the time ? (also part 1 because it took me further than I expected 😬) Couchbase recently introduced support for Vector Search. And I have been looking for an excuse to play with it. As it turns...
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...