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Google's New Chip Designed for AI (and IoT) at the Edge
Google recently announced Edge TPU, an application-specific integrated circuit (ASIC) designed to do exactly what its name suggests: run AI "on the edge" -- something often needed for large machine learning and training projects, as well as time-sensitive Internet of Things (IoT) projects.
Edge computing is a method of distributed computing designed to achieve increased real-time performance and bypass bottlenecks by having the processing take place as close to where the data is stored as possible, instead of first moving the data to, for example, a centralized cloud location. It is often seen as an ideal solution for high-data projects with intense and time-sensitive processing.
"With the explosive growth of connected devices, combined with a demand for privacy/confidentiality, low latency and bandwidth constraints, AI models trained in the cloud increasingly need to be run at the edge," Google commented on the chip's announcement Web site. "It delivers high performance in a small physical and power footprint, enabling the deployment of high-accuracy AI at the edge."
According to Google, the Edge TPU's open nature complements a number of uses and architectures: "It augments Google's Cloud TPU and Cloud IoT to provide an end-to-end (cloud-to-edge, hardware + software) infrastructure."
Google noted that when Edge TPU is released (no date was given), it will be designed to work with the company's open source TensorFlow Lite and will be supported by its Cloud IoT Edge product.
Interested parties can request early access (currently underway) here.
About the Author
Becky Nagel serves as vice president of AI for 1105 Media specializing in developing media, events and training for companies around AI and generative AI technology. She also regularly writes and reports on AI news, and is the founding editor of PureAI.com. She's the author of "ChatGPT Prompt 101 Guide for Business Users" and other popular AI resources with a real-world business perspective. She regularly speaks, writes and develops content around AI, generative AI and other business tech. Find her on X/Twitter @beckynagel.