Businesses have spent decades trying to make better decisions by collecting and analyzing structured data. New AI technologies, including probabilistic programming, Bayesian nonparametrics, and deep learning, are beginning to transform this process. Richard Tibbetts offers a broad overview of these technologies, emphasizing the new organizational capabilities that they create.
Richard covers academic projects for AI-assisted data science, such as BayesDB and the Automated Statistician, as well as emerging technology from multiple startups, highlighting AI that guides business analysts to ask statistically sensible questions and lets junior data scientists answer questions in minutes that previously took trained statisticians hours. Along the way, Richard explains how AI is used to answer questions about the probable implications of messy structured data by translating business questions of interest into queries and using AI assistance to answer them via a combination of open source and commercial tools.
Richard Tibbetts is currently a Principal Product Manager at Tableau. He was founder and CEO of Empirical Systems (acquired by Tableau 2018), a MIT spinout building an AI-based data platform that provided decision support to organizations that use structured data. Prior to Empirical, he was founder and CTO of StreamBase, a CEP company (acquired by TIBCO 2013), as well as a visiting scientist at the Probabilistic Computing Project at MIT.
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