Paul G. Allen

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Vulcan Inc.’s Project Halo is a multi-staged effort to create a Digital Aristotle, an application that will encompass much of the world's scientific knowledge and be capable of applying sophisticated problem-solving to answer novel questions. Vulcan envisions two primary roles for the Digital Aristotle: as a tutor to instruct students in the sciences, and(More)
The Halo Pilot, a six-month effort to evaluate the state-ofthe-art in applied Knowledge Representation and Reasoning (KRR) systems, collaboratively developed a taxonomy of failures with the goal of creating a common framework of metrics against which we could measure interand intrasystem failure characteristics of each of the three Halo knowledge(More)
<lb>As statistical machine learning algorithms and techniques<lb>continue to mature, many researchers and developers see<lb>statistical machine learning not only as a topic of expert<lb>study, but also as a tool for software development. Extensive<lb>prior work has studied software development, but little prior<lb>work has studied software developers(More)
n 1975, when relatively powerful microprocessors first became available, many young entrepreneurs—including myself—were inspired to create companies, platforms, and programming tools that helped make computing available to everyone. This in turn helped spark the information revolution. Today, thanks to the increasing sophistication, speed, and power of(More)
This qualitative study examined U.S. legal cases where battered mothers living abroad fled with their children to the United States. These women subsequently faced child abduction lawsuits brought by their batterer. The cases are governed by the Convention on Civil Aspects of International Child Abduction (the Hague Convention) which was ratified by the(More)
Explaining how the small molecule auxin triggers diverse yet specific responses is a long-standing challenge in plant biology. An essential step in auxin response is degradation of IAA repressor proteins through interaction with auxin receptors. To systematically characterize diversity in degradation behaviors among IAA|receptor pairs, we engineered(More)
Several principles are useful for econometric forecasters: keep the model simple, use all the data you can get, and use theory (not the data) as a guide to selecting causal variables. But theory gives little guidance on dynamics, that is, on which lagged values of the selected variables to use. Early econometric models failed in comparison with(More)
With high frequency data (e.g., hourly), when decisions are based on lower frequency aggregates (e.g., four-hourly intervals) the possibilities are to aggregate the data then directly forecast the aggregates, or indirectly to estimate the disaggregate series then aggregate the forecasts. No clear principle has emerged concerning this choice, and past(More)