AI news for: Rag
Explore AI news and updates focusing on rag for the last 7 days.
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Build a Log Analysis Multi-Agent Self-Corrective RAG System with NVIDIA Nemotron
Logs are the lifeblood of modern systems. But as applications scale, logs often grow into endless walls of text—noisy, repetitive, and overwhelming. H...
TL;DR
NVIDIA's AI-powered log analysis solution uses a multi-agent RAG system to automate log parsing, relevance grading, and self-correcting queries.
Key Takeaways:
Key Takeaways:
- The solution can be used by various teams such as QA, Engineering, DevOps, CloudOps, and Platform/Observability managers to quickly pinpoint issues and improve productivity.
- The system combines a retrieval-augmented generation (RAG) pipeline with a graph-based multi-agent workflow to unify heterogeneous log streams and surface the most relevant snippets.
- The solution can be extended into other areas such as bug reproduction automation, observability dashboards, and cybersecurity pipelines, reducing mean time to resolve (MTTR) and improving developer productivity.
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Community talk
Open-source RAG routes are splintering — MiniRAG, Agent-UniRAG, SymbioticRAG… which one are you actually using?
Multi-modal RAG at scale: Processing 200K+ documents (pharma/finance/aerospace). What works with tables/Excel/charts, what breaks, and why it costs way more than you think
I made a multimodal local RAG system with LM Studio
Building highly accurate RAG -- listing the techniques that helped me and why