I-Corps: Factor graph computing for data-driven decision-making

I-Corps项目的更广泛的影响和商业潜力是使机器学习和预测分析的力量民主化，以帮助非工程业务人员实现其数据的全部价值。实现这一点将在所有级别上推动更好的组织决策制定，并为各种类型和各种规模的商业和政府组织创造额外的业务价值。使用大数据分析的数据驱动决策具有巨大的前景，但在很大程度上仍未实现，主要原因是，以目前的形式，除了技术最先进的组织外，所有人都负担不起。数据驱动型企业的生产率提高了5-6%，每年可能在全球范围内增加3万亿美元的价值。制造业、零售、金融、医疗保健、安全和政府服务等广泛行业将看到重大的商业影响，包括更高的生产力、更好的资源利用以及加速新产品、服务和技术的部署。通过使商业和政府机构更有效地利用其数据和资源，企业和政府机构将提高生产率，更有效地利用其人员，提高其竞争力，消除浪费资源，同时增加产品和服务的流动，造福于整个社会。I-Corps项目基于突破性技术，旨在实现可扩展、灵活且易于使用的数据处理基础设施。在最高层次上，构建这样一个平台需要：(a)提出正确的抽象或语言，以适应各种规模的计算；(b)实施架构以实现大规模计算；(c)从“沙盒”或“原型”到生产环境的能力；(d)在异构数据环境中即时工作的能力。我们提出了一种新的计算语言，称为因子图计算。这样的计算框架是“图灵完备”的。因子图计算允许大规模地执行数据转换、预测建模和优化，以支持数据驱动的决策。这样的平台消除了对数据工程的需求，提供了即时构建预测模型的灵活性，允许通过引入新数据集进行无缝发展，并且需要最少的支持来维护基础设施并允许大规模生成说明性决策。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is to democratize the power of machine learning and predictive analytics to help non-engineering business personnel realize the full value of their data. Enabling this will drive better organizational decision making at all levels and the creation of additional business value for commercial and governmental organizations of all kinds, and of all sizes. Data-driven decisions using big data analytics holds massive promise, but has largely remained unfulfilled primarily because, in its current form, it is unaffordable to all but the most technologically advanced organizations. Data-driven businesses have 5-6% higher productivity and can potentially add $3 Trillion in value globally, per year. A wide range of sectors, such as manufacturing, retail, finance, healthcare, security, and governmental services will see significant commercial impact including higher productivity, better utilization of resources, and the acceleration of the deployment of new products, services, and technologies. By enabling commercial and governmental entities to more effectively utilize their data and resources, businesses and government agencies will increase their productivity, more effectively utilize their personnel, improve their competitiveness, and eliminate waste resources while increasing the flow of products and services that benefit society at large. This I-Corps project is based on ground breaking technology meant to realize a scalable, flexible and easy-to-use data-processing infrastructure. At the highest level, building such a platform requires: (a) coming up with the right abstraction or language that accommodates all sorts of computation at scale; (b) implementing the architecture to realize such computation at scale; (c) the ability to go from "sandboxing" or "prototyping" to a production environment instantly; and (d) the ability to work in heterogenous data environments instantly. We have put forth a novel computational language, called factor graph computing. Such a computation framework is "Turing complete". Factor graph computing allows for performing data transformation, predictive modeling, and optimization at scale to enable data-driven decisions. Such a platform eliminates the need for data engineering, provides flexibility to build predictive models instantly, allows for seamless evolution by bringing in new datasets in the mix, and requires minimal support to maintain the infrastructure and allow for generating prescriptive decisions at scale.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.