Introduction to programmatic labeling
Labeling data manually has become one of the biggest blockers for building AI applications. Hand-labeling data is slow, error-prone, and risks data privacy. Programmatic labeling techniques, developed at the Stanford AI Lab by the Snorkel AI team, automate the labeling process to generate massive, high-quality datasets in minutes. Programmatic labeling has been proven to cut down AI application development time from weeks or months to minutes or days while keeping data in-house.
This webinar will cover
- The limitations of current labeling strategies and why a lack of labeled training data is holding back AI application development.
- What programmatic labeling is and how it works with examples from financial services, healthcare, and more.
- Applications of programmatic labeling that resulted in more accurate models in dramatically less time, allowing models to reach production faster with far less development cost.
- A short demonstration of data-centric AI development in Snorkel Flow powered by programmatic labeling, including automated suggestions, guidance, and integration with foundation models such as GPT-3.
Co-founder and Head of Technology