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.
Geeky Gadgets

Unlock Next-Level RAG Performance with the Jina v4 Embedding Model

What if the key to unlocking next-level performance in retrieval-augmented generation (RAG) wasn’t just about better algorithms or more data, but the embedding model powering it all? In a world where ...
InfoQ

Bridging Modalities: Multimodal RAG for Advanced Information Retrieval

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...
Geeky Gadgets

Supercharge RAG Projects with DeepSeek R1 AI Reasoning Model

Have you ever found yourself frustrated by incomplete or irrelevant answers when searching for information? It’s a common struggle, especially when dealing with vast amounts of data. Whether you’re ...
InfoWorld

What is retrieval-augmented generation? More accurate and reliable LLMs

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...