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You might have heard of Drew Purves before. As head of the Computational Ecology and Environmental Science Group at Microsoft Research Cambridge, he has gained attention for a number of his projects, from modeling forest dynamics to FetchClimate, that use big data and build models to make predictions about future environmental conditions.
He’s back at TechFest this year with a different kind of project. Called Predictive Decision-Making at the Speed of Thought, this effort provides the fundamental research needed to build predictive models for many different types of data, not just the environmental. The goal is to generalize the approach he has been pursuing to make such tools available to a broad range of organizations and businesses.
“In the environmental sciences where we work, but also much more broadly, there’s a lot of demand for the pipeline that goes from big data through models to predictions of important things,” Purves explains. “We know, fundamentally, how to do that, but the technical barriers at the moment are so high that it’s the domain of specialist experts, which, in turn, means that it’s only the world’s largest organizations that can afford to support that kind of data-to-prediction pipeline.”
