Edge TPU
Google’s purpose-built ASIC designed to run
inference at the edge.
AI at the edge
AI is pervasive today, from consumer to enterprise applications.
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. Edge TPU is Google’s purpose-built ASIC
designed to run AI at the edge. It delivers high performance in a
small physical and power footprint, enabling the deployment of
high-accuracy AI at the edge.
End-to-end AI infrastructure
Edge TPU complements Cloud TPU and Google Cloud services to
provide an end-to-end, cloud-to-edge, hardware + software
infrastructure for facilitating the deployment of customers'
AI-based solutions.
High performance in a small physical and power footprint
Thanks to its performance, small footprint, and low power,
Edge TPU enables the broad deployment of high-quality AI at
the edge.
Co-design of AI hardware, software and algorithms
Edge TPU isn't just a hardware solution, it combines custom
hardware, open software, and state-of-the-art AI algorithms
to provide high-quality, easy to deploy AI solutions for the
edge.
A broad range of applications
Edge TPU can be used for a growing number of industrial
use-cases such as predictive maintenance, anomaly detection,
machine vision, robotics, voice recognition, and many more.
It can be used in manufacturing, on-premises, healthcare,
retail, smart spaces, transportation, etc.
An open, end-to-end infrastructure for deploying AI solutions
Edge TPU allows you to deploy high-quality ML inferencing
at the edge, using various prototyping and production
products from
Coral.
The Coral platform for ML at the edge augments Google's
Cloud TPU and Cloud IoT to provide an end-to-end
(cloud-to-edge, hardware + software) infrastructure to
facilitate the deployment of customers' AI-based solutions.
In addition to its open-source TensorFlow Lite programming
environment, the Coral platform provides a complete
developer toolkit so you can compile your own models or
retrain several Google AI models for the Edge TPU, combining
Google's expertise in both AI and hardware.
Edge TPU complements CPUs, GPUs, FPGAs, and other ASIC
solutions for running AI at the edge.
Infrastructure that works with you
By
connecting edge tools with Google Cloud, you can deploy
solutions that can bridge the functionality of the cloud
with the availability of edge computing.
Edge TPU features
This ASIC is the first step in a road map that will
leverage Google's AI expertise to follow and reflect in
hardware the rapid evolution of AI.
Take the next step
Build with Edge TPU using the
development board, which includes an Edge TPU SoM and a
carrier board.
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