D!3#A:AO/1:QO!3S61E|B,YDQ^W{T
SYSTEM PROCESSING...
D!3#A:AO/1:QO!3S61E|B,YDQ^W{T
SYSTEM PROCESSING...
Posted: 2025-05-22 18:09:35 UTC
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
Status
Last Updated
2025-05-22 18:09:56 UTC
Verified By
Rollup News
Retrieval-Augmented Generation (RAG) has evolved into a complex design space with various architectures, including Naive RAG, RAG + Reranker, Multimodal RAG, Graph RAG, Hybrid RAG, and Agentic RAG. Agentic RAG is paving the way for truly intelligent AI systems with multi-agent collaboration, dynamic tool use, contextual memory, and fully autonomous assistants, making RAG the backbone of real-time, context-aware AI.
Evolution of RAG architectures
Agentic RAG for intelligent AI systems
Multi-agent collaboration in RAG
Dynamic tool use in RAG
Contextual memory in RAG
Autonomous AI assistants powered by RAG
Low precision in Naive RAG
Complexity in implementing advanced RAG architectures
Ensuring effective collaboration between multiple AI agents
Developing dynamic tool use capabilities
Integrating long- and short-term memory for contextual awareness