SiliconANGLE

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data

Kinetica DB Inc., which sells a real-time analytics database for time-series and spatial workloads, took to the stage at Nvidia Corp.’s GTC conference today to unveil a new generative artificial ...

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.
ZDNet

Want generative AI LLMs integrated with your business data? You need RAG

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...

Agents need vector search more than RAG ever did

Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...
ZDNet

RAG can make AI models riskier and less reliable, new research shows

Retrieval-Augmented Generation (RAG) is rapidly emerging as a robust framework for organizations seeking to harness the full power of generative AI with their business data. As enterprises seek to ...
Finextra

How Financial Services Companies Secure Data in a RAG GenAI Environment

Few industries have the competitive pressure to innovate — while under as much public and regulatory scrutiny for data privacy and security — as the financial services sector. So, as companies ...
Computerworld

Despite its ubiquity, RAG-enhanced AI still poses accuracy and safety risks

Though Retrieval-Augmented Generation has been hailed — and hyped — as the answer to generative AI's hallucinations and misfires, it has some flaws of its own. Retrieval-Augmented Generation (RAG) — a ...