Amazon Lookout for Vision now supports visual inspection of product defects at the edge

[Amazon Lookout for Vision](/lookout-for-vision/) is excited to preview support for anomaly detection at the edge. Starting today, you can use your trained [Amazon Lookout for Vision models on the edge](https://docs.aws.amazon.com/lookout-for-vision/latest/developer-guide/models-devices.html) by deploying these models to a hardware device of your choice. Your trained models can be deployed on any NVIDIA Jetson edge appliance or x86 compute platform running Linux with an NVIDIA GPU accelerator. You can use [AWS IoT Greengrass](https://aws.amazon.com/greengrass/pricing/) to deploy and manage your edge compatible customized models on your fleet of devices. AWS IoT Greengrass is an open-source edge runtime and cloud service for building, deploying, and managing device software. Earlier in the year, AWS launched Amazon Lookout for Vision, a machine learning (ML) service that spots defects and anomalies in visual representations of manufactured products using computer vision (CV), allowing you to automate quality inspection. You can easily create an ML model to spot anomalies from your live production line with as few as 30 images for the process you want to visually inspect - with no machine learning experience required. You can use Amazon [Lookout for Vision’s cloud APIs](https://docs.aws.amazon.com/lookout-for-vision/latest/APIReference/Welcome.html) to quickly and accurately detect anomalies like dents, cracks, and scratches. Now, in addition to detecting anomalies in the cloud, you can also use your trained [Amazon Lookout for Vision models on the edge](https://docs.aws.amazon.com/lookout-for-vision/latest/developer-guide/models-devices.html) to detect anomalies. You deploy the same Amazon Lookout for Vision models that you've trained in the cloud onto AWS IoT Greengrass V2 compatible edge devices. You then use your deployed model to perform anomaly detection on premises without having to stream data continuously to the cloud. This allows you to minimize bandwidth costs and detect anomalies locally with real time image analysis. With Amazon Lookout for Vision and AWS IoT Greengrass, you can automate visual inspection with CV for processes like quality control and defect assessment - all on the edge and in real time. You can proactively identify problems such as part damage (like dents, scratches, or poor welding), missing product components, or defects with repeating patterns, on the production line itself - saving you time and money! Customers like Tyson Foods and Baxter International Inc. are discovering the power of Amazon Lookout for Vision to increase quality and reduce operational costs by [automating visual inspection](https://aws.amazon.com/blogs/machine-learning/machine-learning-inference-at-the-edge-using-amazon-lookout-for-vision-and-aws-iot-greengrass/). Amazon Lookout for Vision is available directly via the AWS console as well as through supporting [partners](/lookout-for-vision/partners/) to help customers embed computer vision into existing operating systems within their facilities. Amazon Lookout for Vision on Edge is available in preview today in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Europe (Frankfurt), Asia Pacific (Tokyo), and Asia Pacific (Seoul), with availability in additional regions in the coming months. To learn more and get started, visit the Amazon Lookout for Vision [product page](/lookout-for-vision/).