63% of executives are concerned about LLM hallucinations, a nearly 10% increase compared to 2023. Though rare, incidents of AI tools confidently producing incorrect information regularly go viral, damaging corporate reputations and costing companies valuable time and effort as they race to fix the problematic model.
But with the right infrastructure, LLM hallucinations can be harnessed to improve your AI lifecycle. Learn how to build a comprehensive, reliable observability practice that enables your team to quickly identify hallucinations, use them to pinpoint the source of the problem, and resolve the issue before any real problems arise.
Join DataRobot Field CTO Lisa Aguilar and Justin Swansburg VP, Applied AI to explore:
- The common causes of LLM hallucinations
- The tools you need to successfully govern models in production
- How to troubleshoot LLM hallucinations
Speakers
Lisa Aguilar
Justin Swansburg