retrieval augmentation

About this tag
Retrieval augmentation (RAG) is a technique that grounds AI outputs in external, trustworthy data sources to reduce hallucinations and improve factual accuracy. Discussions on WindowsForum highlight RAG's role in curbing AI fabrications, particularly in enterprise deployments like Microsoft Copilot, where licensed content and tenant-specific grounding help mitigate risks. Real-world experiments, such as a public RAG test involving Shell archive materials, demonstrate both the potential and limitations of retrieval augmentation in handling satire, defamation, and tricky prompts. While RAG reduces but does not eliminate hallucinations, it remains a key strategy for organizations seeking reliable AI-assisted workflows.
  1. AI Satire and Defamation Risk in the Shell Archive: A Public RAG Experiment

    The late‑December experiment staged by long‑time Shell critic John Donovan transformed an old, bitter dispute into a live laboratory for how generative AI, archival persistence, and modern media law collide — and it did so in full public view by publishing both a satirical piece produced with AI...
  2. Trick Prompts and AI Hallucinations: Ground AI in Trustworthy Sources

    The tidy, confident prose of mainstream AI assistants still hides a messy truth: when pressed with “trick” prompts—false premises, fake-citation tests, ambiguous images, or culturally loaded symbols—today’s top AIs often choose fluency over fidelity, producing answers that range from useful to...
  3. Curbing Hallucinations in Copilot: Grounding, RAG, and Enterprise Guardrails

    Microsoft’s Copilot can speed through drafting, summarizing and spreadsheet work with alarming fluency — and that fluency is exactly why hallucinations (confidently wrong answers) are both dangerous and stubbornly persistent. Recent research from OpenAI shows hallucinations aren’t merely...
  4. Reducing AI Hallucinations: Governance and Grounded LLM Deployment

    AI systems are getting more capable, but the stubborn problem of hallucinations — confidently delivered, plausible-sounding falsehoods — remains a clear operational and governance risk for organizations deploying large language models today. Background Hallucinations are not a fringe bug; they...