5 Pitfalls of Large Language Models in Production and How to Solve Them

Explore the challenges and solutions for deploying Large Language Models (LLMs) in production environments in this 46-minute conference talk by Devanshi Vyas, Co-founder at Censius. Discover the complexities data scientists face when detecting and mitigating LLM hallucinations, biases, and drifts. Learn about the importance of continuous monitoring to prevent revenue loss, reputational damage, and regulatory non-compliance. Gain insights into real-time monitoring practices that can uncover model issues, detect hallucinations, and identify trends in NLP and Generative AI models. Understand strategies for improving model performance, optimizing operational costs, and minimizing technical debt. Key takeaways include the main challenges of LLMs in production, the necessity of continuous risk monitoring, and the role of AI Observability with embedding visualizations for proactive troubleshooting. This talk was presented at the 2023 Oktoberfest Data Science Festival in London, organized by the Data Science Festival community.

5 Pitfalls of Large Language Models in Production and How to Solve Them