Strategies for Reducing Hallucinations
Implement methods to minimize factual inaccuracies and fabricated information generated by LLMs.
What are LLM Hallucinations?
Welcome! In this lesson, we'll tackle a common challenge with Large Language Models (LLMs): hallucinations.
An LLM hallucination occurs when the model generates information that is factually incorrect, nonsensical, or completely fabricated, yet presents it as if it were true. It's like the AI is confidently making things up!
Why LLMs 'Hallucinate'
LLMs are trained to predict the next most probable word based on patterns in vast amounts of text data. They don't 'know' facts in the human sense.
- Sometimes, they lack sufficient or relevant information.
- They might extrapolate beyond their training data.
- They prioritize sounding coherent and confident over being factually accurate.
Understanding this helps us design better prompts to guide them.
All lessons in this course
- Identifying and Reducing Bias
- Strategies for Reducing Hallucinations
- Ethical Considerations in Prompting