Businesses have spent decades trying to make better decisions through the complete understanding of data. New technologies make Bayesian inference and generative modeling more accessible to business analysts. But the ability to rapidly quantify uncertainty, simulate new data, and understand direction, magnitude, and confidence of effects creates new communications challenges. Richard Tibbetts shares techniques for capturing domain knowledge and making findings actionable for decision makers utilizing the explanatory powers of transparent AI.
Richard Tibbetts is CEO of Empirical Systems, an MIT spinout building an AI-based data platform that provides decision support to organizations that use structured data. Previously, he was founder and CTO at StreamBase, a CEP company that merged with TIBCO in 2013, as well as a visiting scientist at the Probabilistic Computing Project at MIT.
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