Bridging the Last Mile: Applying Foundation Models with Data-Centric AI

Large language models (LLMs) and Foundation models (FMs) represent one of the most powerful new ways to build AI models; however, they still struggle to achieve production-level accuracy “out of the box” on complex, high-value, and/or dynamic use cases, often “hallucinating” facts, propagating data biases, and misclassifying domain-specific edge cases. This “last mile” problem is always the hardest part of shipping production AI applications, especially in the enterprise and while FMs provide powerful foundations, they do not “build the house”.

In this webinar, Snorkel AI CEO and co-founder Alex Ratner will take live audience questions and provide an overview of how solving the “last mile” problem is increasingly all about the data and provide data-centric approaches you can use to adapt LLMs to your specific use case or to build custom, domain-specific LLMs with your data.