Using Advanced ML Methods For Data Labeling with Superb AI

Hyun Kim, CEO, Superb AI

For companies and application developers trying to build and deploy models for inventory management, autonomous checkout, item detection, and even smart shopping, critical bottlenecks can occur across the wider scope of model and data ops. In particular, because retail AI models need to account for a myriad of edge device scenarios, ranging from identifying device location to meeting dynamic monitoring requirements, ML teams need to have the ability to rapidly create and deliver high-quality datasets.

I will dive into SuperbAI’s ML-first approach to data labeling, demonstrating how our advanced transfer learning and few-shot learning autoML solution has allowed ML teams of all sizes to label, audit, and deliver training datasets in days.