Scaling Past Rule-Based Systems at the Petabyte Level

Discover how weak supervision techniques can scale beyond traditional rule-based and expert-curated systems for solving core Natural Language Processing (NLP) problems on massive datasets exceeding a petabyte. This 25-minute conference talk by Snorkel AI explores innovative approaches to handling large-scale data challenges in AI and machine learning. Gain insights into cutting-edge methodologies for processing and analyzing vast amounts of textual information, and learn how these techniques can revolutionize NLP applications across various industries. Explore the potential of weak supervision in overcoming limitations of conventional systems and unlocking new possibilities in data-centric AI development.