The speakers discuss the challenge of explaining what the AI model did in the first place, even if the answer is incorrect. They mention the importance of explainability in generative AI and propose regenerating specific parts of incorrect answers until they are correct.
Adam Wenchel is the CEO of Arthur, a company with a platform that gives you an immediate comprehensive AI performance solution across LLMs, Computer Vision, Tabular Data, and NLP.
Adam and the team have been making AI observable for almost 5 years with Arthur. Arthur has raised over $60 million from a legendary group of investors including Index Ventures, Greycroft Partners, Work-Bench, and others. An equal list of impressive customers they’ve served includes Humana and Plaid, among others.
Listen and learn
- How Adam started his career in AI
- How he helped map out Capital One’s early AI strategy
- The value of evaluating AI model performance
- How Arthur launched its first LLM-specific product and what the team learned
- How to monitor the performance of an LLM model in production and which questions to ask when evaluating it
- The lessons from growing a startup that nobody talks about
References in this episode…