Teaching Home Robots

At TRI, our goal is to make breakthrough capabilities in Artificial Intelligence (AI). Despite recent advancements in AI, the large amount of data collection needed to deploy systems in unstructured environments continues to be a burden. Data collection in computer vision can be both quite costly and time-consuming, largely due to the process of annotating. Annotating data is typically done by a team of labelers, who are provided a long list of rules for how to handle different scenarios and what data to collect. For complex systems like a home robot or a self-driving car, these rules must be constantly refined, which creates an expensive feedback loop.