AI for Small Businesses and Consumers: Applications and Innovations

Small businesses are the lifeblood of the U.S. economy, representing an astounding 99.9 percent of all businesses, creating two-thirds of net new jobs, and accounting for 44 percent of economic activity. Yet, 50 percent of small businesses go out of business in the first 5 years. What's behind this dismal statistic? Among the top contributing factors is cash flow management. Owners who cannot efficiently manage the inflow and outflow of cash are almost certain to fail. And, those who can are more likely to break through the statistical 5-year barrier to build thriving businesses. In this talk, we'll describe novel applications of artificial intelligence and large-scale machine learning aimed at addressing the problem of forecasting cash flow for small businesses. These are sparse, high-dimensional correlated time series. We'll present new results on forecasting this type of time series, using scalable Gaussian Processes with kernels formed through the use of deep learning. These methods yield highly accurate predictions but also include a principled approach for generating confidence intervals.