Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the critical role of data-centric development in achieving production-level AI accuracy in this 48-minute talk by Snorkel AI CEO and Co-Founder Alex Ratner. Discover why large language models and Foundation Models (FMs) struggle with complex, high-value, and dynamic use cases, often resulting in hallucinations, data biases, and misclassifications. Learn about the "last mile" problem in shipping real AI applications, particularly in enterprise settings, and understand why FMs provide powerful foundations but don't complete the entire solution. Gain insights into modern data-centric AI development approaches for solving these challenges, covering all stages from pre-training to instruction-tuning, alignment, task-specific fine-tuning, and distillation. Get a preview of state-of-the-art techniques and tools for handling data-centric development with foundation models, equipping you with knowledge to overcome the hardest part of implementing AI in production environments.