Ryan Kolln

Ryan Kolln, CEO of Appen, discusses the critical role of human evaluation in training AI models. He explains why traditional benchmarks fall short, emphasizing the need for user-centered measures. Kolln highlights how curated human evaluators provide richer insights than random feedback, ensuring AI's cultural relevance through localized data. He also covers the evolution from supervised learning to large language model evaluations, and the synergy between AI evaluators and human annotators in enhancing quality control and model performance.