BerriAI / litellm
github.com·3d ago
Developer Tools
Databricks Blog·Aug 13·5 min read
What are AI Hallucinations?
TL;DR
AI hallucinations are confident but incorrect outputs generated by models like chatbots and image generators, posing risks in various applications. These inaccuracies stem from the predictive nature of AI, where errors can escalate into significant falsehoods.
✦ Why It Matters
Evaluate your AI deployment strategies to mitigate risks associated with hallucinations today.
Key Takeaways
- Establish clear boundaries for AI model outputs to reduce hallucinations.
- Integrate human review for high-stakes AI applications.
- Utilize retrieval-augmented generation to connect models with trusted data.
- Continuously monitor and evaluate AI performance to identify failure patterns.
How It Works
Generative AI models predict the next likely word based on training data, which can lead to plausible-sounding but incorrect outputs. Techniques like retrieval-augmented generation can help connect models to verified knowledge sources, improving accuracy.