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Using AI to solve location and mobility problems

In an abstract sense, location industries—industries, such as real estate and retail, with salient location components and interests—are essentially concerned with signal detection. The better that one is at exploiting data to identify hidden patterns and signals, the greater is the payoff, regardless of the domain, whether it be investment management, site selection, underwriting, or asset valuation. A truly revolutionary and effective strategy will therefore involve aggregating massive amounts of heterogeneous traditional and nontraditional signals, leveraging AI and machine-learning algorithms, and adopting a quantitative and scientific approach. We explore how we at use AI to solve location and mobility problems.

Tech founder. Mathematician. AI scientist. Economist. Engineer. Writer. Artist. Musician. Swimmer. Boundlessly curious person. Whether as a researcher at LSE, a strategic advisor to Abbott Laboratories, or the mathematical mind behind a boutique consulting firm, Chlump has made a career of developing novel strategies and building mathematical models, technologies, and algorithms. He has written on a variety of subjects ranging from mathematics to multilateral refugee and asylum policy. The goal of his PhD was to revolutionize the field of game theory. His current goal is to revolutionize the world of location and mobility. He holds a BA in Economics from Northwestern University, an MA in Philosophy from NYU, and a PhD in Mathematics from LSE.

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