Neuromorphic computing in the edge: merging cyber and physical

G. Gielen
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Abstract

In today’s emerging world, both humans and objects are continuously connected, collecting and communicating data. The rising number of applications relying on smart ICT technology includes autonomous vehicles, industry 5.0, biomedical wearables and implants, environmental sensing, smart houses and offices, etc. With all these data, local computation in the edge has become a necessity to limit data traffic and response latency. Embedding AI processing in the edge may add high levels of smart autonomy to these systems. Progress in nanoelectronic technology in combination with emerging neuromorphic, event-driven architectures with dynamic learning capabilities allow to do this in a power- and hardware-efficient way. This keynote will explore some solutions being developed today, and illustrate them with some practical examples of integrated circuits that are on the verge of merging the cyber and the physical worlds.
边缘的神经形态计算:融合网络和物理
在当今的新兴世界中,人类和物体都在不断地连接,收集和交流数据。依赖于智能ICT技术的应用越来越多,包括自动驾驶汽车、工业5.0、生物医学可穿戴设备和植入物、环境传感、智能家居和办公室等。有了所有这些数据,边缘的本地计算已经成为限制数据流量和响应延迟的必要条件。在边缘嵌入人工智能处理可能会为这些系统增加高水平的智能自主性。纳米电子技术的进步与新兴的神经形态、具有动态学习能力的事件驱动架构相结合,可以以一种节能和硬件高效的方式实现这一目标。本主题演讲将探讨当今正在开发的一些解决方案,并通过一些集成电路的实际例子来说明这些解决方案,这些集成电路即将融合网络和物理世界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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