Automating Data Collection at Morningstar
We think of self-driving cars from Tesla, intelligent Google search or even robot overlords from Battlestar Galactica as visual representations of Machine Learning—AI. These areas have certainly experienced innovation through AI but they should just be a starting point for our imagination. The opportunities for applying Machine Learning to real world problems are endless especially with cost effective compute that can be easily provisioned. At Morningstar, we’re leveraging Machine Learning to collect financial data on many different instrument types across global markets. A task that had been executed manually in the past is now becoming highly optimized to deliver scale and quality by leveraging Machine Learning. We’re building a self-sustaining model improvement lifecycle that includes automated continuous feedback collection, retraining and deployment. We’re helping form a symbiotic relationship between human data collectors and the Machine. The manual workflow is optimized by delivering inferences to a human being who can now process far more data and be able to focus on their domain instead of parsing through individual datapoints.
Session ID: LI1518 Presentation Type: Live Session (Replay Available)
Date / Time: [Day 5] Fri. Sep. 18, 2020 @ 15:00 ET (US)
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