Matthew Groves, DevRel engineer at Couchbase, and Nithish Raghunandanan, senior developer advocate at Couchbase, joined DBTA's webinar Coding With AI: Vector Search and RAG-Building with AI, and AI ...

Vector Shift Platform: A Practical Example To showcase the practical application of the ChatGPT-o1 models and RAG techniques, ChatGPT-o1 Series AI have now been added to the Vector Shift platform.

Redis, the in-memory data structure store, has recently released its enhanced Redis Query Engine. This comes at a time when vector databases are gaining prominence due to their importance in retrieval ...

Teradata is adding vector support to its platform in the form of a new Enterprise Vector Store, an in-database offering, to enable and augment use cases that require retrieval augmented generation ...

The new vector search capability will leverage vector embeddings stored directly in the JSON document to provide more relevant results for searches. Vector embeddings are mathematical representations ...

Agentic RAG isn’t a hypothetical concept either. It’s already being used by one of Vectorize’s early users, AI inference silicon startup Groq, which recently raised $640 million.

At the heart of Vectorize’s platform is a “production-ready RAG pipeline” that makes it possible to transform unstructured data into optimized vector search indexes.

In this video, I'll be showing you how to build your own custom AI agent within Python using Retrieval Augmented Generation (RAG) and LangChain. Even if you're an intermediate Python user, this ...

In an ongoing effort to improve the usability of AI vector database searches within retrieval-augmented generation (RAG) systems by optimizing the use of solid-state drives (SSDs), KIOXIA today ...