•Billy Rutledge (Director) and Vikram Tank (Product Mgr), Coral Team•3 min read•beginner•
--
•View OriginalOverview
The article introduces Coral, a platform designed for developing intelligent devices with local AI. It highlights the components and tools available for building, training, and deploying neural networks locally, emphasizing performance, privacy, and ease of prototyping.
What You'll Learn
1
How to build intelligent devices using the Coral platform
2
Why local AI enhances privacy and performance in applications
3
When to use Edge TPU for machine learning inferencing
Key Questions Answered
What is the Coral platform and its purpose?
Coral is a platform developed by Google for building intelligent devices with local AI. It provides a complete toolkit that includes hardware components and software tools to create, train, and run neural networks locally, ensuring high performance and privacy.
How does the Edge TPU enhance machine learning applications?
The Edge TPU is a small ASIC designed by Google that enables high-performance machine learning inferencing for low-power devices. It can execute advanced mobile vision models like MobileNet V2 at over 100 frames per second, making it ideal for real-time applications.
What hardware components are included in the Coral platform?
Coral includes several hardware components such as the Coral Dev Board, Coral Camera Module, and Coral USB Accelerator. These components are designed for easy integration and prototyping, allowing developers to scale their projects to production.
How can Coral products be integrated with Google Cloud IoT?
Coral products can be used with Google Cloud IoT, which combines cloud services with an on-device software stack for managed edge computing. This integration allows developers to leverage machine learning capabilities in connected devices.
Key Statistics & Figures
Mobile vision model performance
100+ fps
The Edge TPU can execute state-of-the-art mobile vision models like MobileNet V2 at over 100 frames per second.
Technologies & Tools
Some links below are affiliate links. We may earn a commission if you make a purchase.
Platform
Coral
Used for building intelligent devices with local AI.
Hardware
Edge Tpu
Provides high-performance machine learning inferencing for low-power devices.
Software
Tensorflow
Core framework for developing and training machine learning models.
Software
Tensorflow Lite
Used for running machine learning models on mobile and edge devices.
Key Actionable Insights
1Leverage the Coral platform for rapid prototyping of AI applications.Coral's toolkit is designed for quick development cycles, allowing engineers to test and iterate on their ideas efficiently. This is particularly beneficial for startups and developers looking to innovate in the AI space.
2Utilize the Edge TPU for optimizing machine learning models on low-power devices.The Edge TPU's ability to run models at over 100 fps makes it suitable for applications requiring real-time processing, such as computer vision tasks in mobile devices.
3Explore the pre-trained models provided by Coral to kickstart your projects.Coral offers a variety of pre-trained models that can be used out of the box, which can significantly reduce the time needed to develop machine learning applications.
Common Pitfalls
1
Failing to properly integrate the Edge TPU can lead to suboptimal performance.
Developers should ensure that their models are quantized and compiled correctly for the Edge TPU to maximize performance and efficiency.
Related Concepts
AI
Iot
Tensorflow Lite
Machine Learning
Edge Tpu