10 Critical LLM Blunders - Detect and Fix with LLM Judges
Dive deep into the intricacies of LLM-based applications with this comprehensive technical webinar
About This Webinar
Dive deep into the intricacies of LLM-based applications with this upcoming webinar. Join our expert speakers, who have spent the majority of the last three years analyzing and addressing failure modes in LLM systems across various industries. This session will guide you through detecting, blocking, and remedying the most common yet critical errors that undermine the reliability of AI applications.
This webinar is tailored for a highly technical audience aiming to refine their approach to managing and optimizing LLM-based systems.
Key Takeaways
- Learn about the frequent and critical blunders in LLM outputs that could be affecting your systems
- Discover cutting-edge techniques for identifying subtle yet significant errors that standard methods often miss
- Explore automated strategies for effectively correcting detected errors, enhancing system resilience
- Understand how to deploy LLM judges for ongoing monitoring and evaluation of AI outputs
Who Should Attend
- ML Engineers working with LLM-based applications
- Data Scientists implementing AI systems
- Technical leads responsible for AI system reliability
- DevOps engineers managing AI/ML deployments
- Anyone interested in LLM error detection and correction
About the Speakers
Our expert speakers have spent the majority of the last three years analyzing and addressing failure modes in LLM systems across various industries. They bring deep practical experience in detecting, blocking, and remedying the most common yet critical errors that undermine the reliability of AI applications.
Watch the Recording
This webinar has concluded. Fill out the form below to access the recording and learn about the 10 critical LLM blunders.
Stay Updated
Subscribe to our newsletter for monthly updates on LLM evaluation trends and upcoming webinars.
