Reducing Hallucinations in Conversational Systems
summary
Claims that prompt techniques cut hallucinations without retraining sit alongside concrete numbers: GPT-3 has 175 billion parameters. Gives specific tools and workflows: MIRACLE integrates external tools like a calculator and databases to verify facts. Notes costs and tradeoffs: fine-tuning and retraining reduce bias but are expensive, while zero/few-shot and chain-of-thought prompts are quick experiments. Shows a built example where tool integration fixes math errors and improves factual reliability.
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chapters (8)
- 0:00Introduction and Agenda
- 0:18Understanding Large Language Models (LLMs)
- 1:30The Transformer Architecture
- 3:27Ethical AI: Principles and Challenges
- 4:18Addressing Bias in AI
- 6:01Understanding and Mitigating Hallucinations
- 9:29Prompt Engineering Techniques
- 13:38Conclusion and Key Takeaways
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