VentureBeat

Vector database company Qdrant wants RAG to be more cost-effective

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More More companies are looking to include retrieval augmented generation (RAG ...

Databricks built a RAG agent it says can handle every kind of enterprise search

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
InfoQ

Redis Improves Performance of Vector Semantic Search with Multi-Threaded Query Engine

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
The Manila Times

VAST Data Introduces End-to-End Fully Accelerated AI Data Stack with NVIDIA

VAST AI OS will leverage NVIDIA libraries to accelerate both compute and data services for RAG, vector search, real-time SQL, ...
SiliconANGLE

Couchbase’s database gets support for vector search and retrieval-augmented generation

Cloud database-as-a-service provider Couchbase Inc. today added some powerful new capabilities to its platform that should enhance its ability to support more advanced generative artificial ...
WinBuzzer

Databricks KARL Agent Tackles All Enterprise Search Types via RL

Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower cost than frontier models.
InfoWorld

Oracle’s Database 23c gets vector search to underpin generative AI use cases

The semantic search capabilities added to the database offering include a new vector data type, vector indexes, and vector search SQL operators. Oracle is planning to add vector search capabilities to ...