Preventing LLM Hallucinations

In this session attendees learned how to make AI truly dependable in critical operations. They were joined by John Bohannon, VP of Data Science at Primer, for an in-depth exploration of RAG-Verification (RAG-V) — a system designed to reduce hallucination rates in Large Language Models (LLMs) by 100x.

In this session attendees learned:

• How RAG-V detects and corrects factual errors, using a fact-checking approach that’s tailored for complex, high-stakes environments.
• How Primer breaks down intricate questions into individual claims, allowing for real-time, automated fact-checking that you can trust.
• How to apply actionable insights for implementing trustworthy AI practices within your own data operations. 

If you’re ready to explore the future of trustworthy AI and elevate your data operations, view the on-demand webinar today!