Episode 126: AI Hallucinations
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Episode 126: AI Hallucinations
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Podcast Summary:
How do we stop AI from making things up? On The AI Podcast, we unravel the cutting-edge strategies being deployed to eliminate AI hallucinations and build truly trustworthy Large Language Models (LLMs).
This episode is your masterclass in AI factuality. We explore the full stack of solutions:
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Architectural Fixes: How Retrieval-Augmented Generation (RAG) grounds AI in truth and why new training objectives are penalizing confident errors.
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Smarter Prompting: Unlocking techniques like Chain-of-Thought (CoT) and Structured XML Prompting to force clearer, more logical reasoning from any model.
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Self-Correction: Discovering how models can now verify their own work using methods like Chain of Verification (CoVe) and Hallucination Correction Models.
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Governance & Security: Framing it all within essential AI Risk Management Frameworks (NIST, ISO 42001) and the critical role of AI Red Teaming.
If you're building, deploying, or just relying on AI, this is your essential guide to ensuring the outputs you get are accurate, reliable, and grounded in fact.