How Custom Workflows, Real Time Functionality And Predictive AI Decrease Time-To-Value And Increase ROI In Data Enrichment

Abstract: 

The age-old adage "time is money" is perhaps more applicable today than during anytime in history. In this presentation, iMerit deep learning engineer Hrishikesh Hippalgaonkar talks about how a transformational, solutions-oriented approach to addressing data labeling problems will decrease Time-to-Value and increase ROI in the Artificial Intelligence and Machine Learning ecosystems. He will speak specifically of solutions mapping to custom workflows, real-time functionalities and predictive AI and how these solutions factor into the data labeling pipeline for AI and Machine Learning. He discusses the need for taking a holistic, solutions-based approach to AI deployments, and why partnering with organizations with vision and the ability to execute at scale are critical to AI success.

Bio: 

iMerit Deep Learning Engineer Hrishikesh Hippalgaonkar, has a MS from USC in Electrical Engineering, with a concentration in Computer Vision and Deep Learning technology. He has a BE in Electronics and Telecommunications from the University of Pune. Before iMerit, Hippalgaonkar was on the teams at Frenzy AI and DreamVu.