A business / market opportunity assessment for hardware concepts & device designs for deep learning (DL)

我们正在开发计算硬件概念和设计，为深度学习（DL）提供比现有商品硬件更快的数据处理能力和更好的能源效率。我们的技术增加了深度学习的复杂性，使得以目前不可能的方式部署深度学习变得可行。我们的目标是可扩展的硬件，可以定制各种设备和应用程序。好处是：1)在桌面/数据中心，我们将通过部署更大和更复杂的深度学习网络以及以更快的速度处理更多输入数据来实现深度学习的进一步创新和复杂化，2)对于移动或嵌入式应用程序，我们将允许i)部署更复杂和准确的深度学习网络，ii)大幅减少能耗，从而提高移动设备的正常运行时间。iii)减少电力需求，使系统更便携，可用于各种场景（例如，自动驾驶汽车，个人辅助等）。我们的设计新颖而独特，并已被证明优于迄今为止提出的同类最佳硬件设计和商业上可用的解决方案2到3个数量级。我们的设计可以为高端桌面/服务器市场或嵌入式/移动/物联网领域提供下一代DL解决方案。这是一份I2I市场评估拨款的申请，旨在接触现场和潜在客户，以适当地确定合适的应用程序，从而确定配置，作为我们创新技术成功商业化的第一步。

We are developing computing hardware concepts and designs that deliver two to three orders of magnitude faster data processing capability and better energy efficiency than existing commodity hardware for Deep Learning (DL). Our techniques enable an increase in DL sophistication making it practical to deploy DL in ways not currently possible. We target scalable hardware that can be tailored to various devices and applications. The benefits are: 1) at the desktop/data-center, we will enable further innovation and sophistication in DL by enabling the deployment of larger and more sophisticated DL networks and the processing of more input data and at faster speeds, 2) for mobile or embedded applications, we will allow i) the deployment of more sophisticated and accurate DL networks, ii) a drastic reduction in energy consumption and thus improvement in up-time for mobile devices, and iii) a reduction in power needs making the system more portable and usable in a variety of scenarios (e.g., autonomous vehicles, personal assists, etc.).Our designs are novel and unique and have been shown to outperform the best in class hardware designs proposed thus far and commercially available solutions by 2 to 3 orders of magnitude. Our designs canenable the next generation of DL solutions be it for the high-end desktop/server market or the embedded/mobile/IoT space. This is an application for an I2I Market Assessment grant to reach out to the field and potential customers in order to appropriately identify appropriate applications and thus the configurations that should be targeted as a first step toward successful commercialization of our innovative technology.