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Thursday, February 27 • 10:55am - 11:20am
Improving models for Oracle Machine Learning using Knowledge Graphs

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What AI requires are disambiguated, highly relevant, and specific, integrated data, flowing to the point of need. What it often gets are single-batch sets, cleaned up to be just good enough, often done manually. Data Scientists are said to spend 80% of their time with clean-up tasks. Often, we have to work with too abstract, disconnected data models that can't keep pace with market dynamics. Semantically enriched data serves as a basis for better data quality and provides more options for feature extraction. IT infrastructure that moves data to the algorithms and applications is failing. Data centric designs do away with these bottlenecks. Semantic AI is the combination of methods derived from symbolic AI and statistical AI. It is not only focused on process automation, but also on intelligence augmentation. We'll outline the path towards self-optimizing machines by demonstrating the interoperability of Knowledge Graph and ML algorithms for better performance and scale.

avatar for Sebastian Gabler

Sebastian Gabler

Director of Sales, Semantic Web Company
Originally trained as Recording Producer with a diploma degree from Berlin University of the Arts (UdK), Sebastian pursues a career in archive- and information management for over 15 years, after spending 5 years in music production for Radio, TV and Recording industry. Sebastian... Read More →

Thursday February 27, 2020 10:55am - 11:20am PST
Bldg 23- Rm 1740 .