SBIR Phase I: An Open Source Platform for Intelligent Virtual Assistants

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力将来自世界上第一个开源智能虚拟助理（IVA）平台的开发和发布。该平台将作为开源软件免费提供给全世界，并将被一组商业产品所包围，其中包括软件的部署和定制以及软件即服务（SaaS）产品，这些产品将允许平台的用户轻松地创建和部署IVAs。除了IVA技术的商业应用之外，该平台的开源版本将有助于围绕IVA技术建立一个健康、活跃的开源社区，使其能够作为机器学习研究平台加以利用，并加速IVA在重要的非商业环境中的采用，如非营利教育和改善残疾人的技术获取。这个小型企业创新研究（SBIR）第一阶段项目将解决重大的计算机系统挑战，涉及在智能虚拟助理（IVA）技术所需的复杂算法组件管道中无缝协调大量计算。为IVAs提供动力所需的计算量足够大，这样的软件系统可能会在由不同服务器类型和加速器平台组成的复杂生态系统组成的大型数据中心基础设施中运行。该项目将通过在IVA平台内构建一个集中的软件机制来解决这些挑战，该机制用于监视作业执行，以促进有效地将IVA计算中的子任务映射到数据中心中可用的硬件资源。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will arise from the development and release of the world's first open source Intelligent Virtual Assistant (IVA) platform. The platform will be made available to the world as open source software free of charge, and will be surrounded by a set of commercial offerings that include the deployment and customization of the software as well as software-as-a-service (SaaS) offerings that will allow users of the platform to painlessly create and deploy IVAs. Beyond the commercial applications of IVA technology, the open source release of the platform will help foster a healthy, active open source community around the IVA technology, allowing it to be leveraged as a machine learning research platform and accelerating IVA adoption in important non-commercial settings such as non-profit education and improving technological access for the disabled.This Small Business Innovation Research (SBIR) Phase I project will address the significant computer systems challenges involved in seamlessly orchestrating the massive amounts of computation among complex pipelines of algorithmic components required to power intelligent virtual assistant (IVA) technologies. The computation required to power IVAs is large enough that such software systems will likely run in large datacenter infrastructures comprised of complex ecosystems of different server types and accelerator platforms. This project will address these challenges by building a centralized software mechanism within the IVA platform for monitoring job execution to facilitate efficiently mapping sub-tasks within the IVA computation to the available hardware resources in the datacenter.