The challenges in using LLM-as-a-Judge - Sourabh Agrawal | Vector Space Talks

Sourabh Agrawal, CEO and Co-Founder of UpTrain AI, discusses the challenges and strategies of using large language models (LLMs) as evaluative tools, specifically in the context of AI chatbots. He emphasizes the importance of cost-effective evaluation, advocating for the use of smaller, cheaper models over expensive ones like GPT-4 to avoid high costs in assessing AI responses. UpTrain, an open-source LLMOps tool developed by Agrawal, aims to address these challenges by providing systematic, real-time evaluation metrics and automated suggestions for improving chatbot interactions. The tool supports various evaluation criteria, including context relevance, response completeness, and user satisfaction, while also offering customization options for specific use cases. Agrawal highlights the necessity of these evaluations in maintaining the integrity of chatbots and preventing undesirable actions such as jailbreaks or false promises. Through demonstrations and discussions, he illustrates how UpTrain's evaluations can help developers refine AI models and ensure they meet business requirements effectively.