AI for large scale AI product development

About this talk

AI development in an enterprise setup is challenging primarily because of the fact that data volumes are never sufficient for the data hungry Deep Learning model training. Data collection & model training goes hand in hand and is an iterative process which is usually ever evolving. Particularly in case of Autonomous driving the scale of data is enormous (in Petabytes/week). Incremental data collection and dealing with all aspects of data management can be very complex without a winning strategy. Giant corporates like “Bosch” intend to leverage these huge data lakes for AI enablement of numerous use cases across multiple domains. And hence it requires a good data strategy. I would talk about a “data loop” strategy, a generalized overview of how AI based tools & processes enable the data loop strategy for large scale product development with a synopsis of autonomous driving domain.