Whether businesses are using machine learning to perform predictive maintenance or create better retail shopping experiences, ML has the power to unlock value across a myriad of use cases. We're constantly inspired by all the ways our customers use Google Cloud AI for image and video understanding--everything from eBay's use of image search to improve their shopping experience, to AES leveraging AutoML Vision to accelerate a greener energy future and help make their employees safer. Today, we're introducing a number of enhancements to our Vision AI portfolio to help even more customers take advantage of AI. Performing machine learning on edge devices like connected sensors and cameras can help businesses do everything from detect anomalies faster to efficiently predict maintenance. But optimizing machine learning models to run on the edge can be challenging because these devices often grapple with latency and unreliable connectivity.

In a recent blog post, Google announced enhancements to a part of its Vision AI portfolio: AutoML Vision Edge, AutoML Video, and the Video Intelligence API. Each received updates to enhance their capabilities. Both AutoML Vision Edge and AutoML Video were both introduced earlier this year, in April, as a part of Google's AI Platform, while the Video Intelligence API introduction dates back a few years prior, with a public beta release in June 2017. We're constantly inspired by all the ways our customers use Google Cloud AI for image and video understanding--everything from eBay's use of image search to improve their shopping experience to AES leveraging AutoML Vision to accelerate a greener energy future and help make their employees safer. With AutoML Vision Edge, developers can train, build and deploy ML models at the edge.

Whether businesses are using machine learning to perform predictive maintenance or create better retail shopping experiences, ML has the power to unlock value across a myriad of use cases. We're constantly inspired by all the ways our customers use Google Cloud AI for image and video understanding--everything from eBay's use of image search to improve their shopping experience, to AES leveraging AutoML Vision to accelerate a greener energy future and help make their employees safer. Today, we're introducing a number of enhancements to our Vision AI portfolio to help even more customers take advantage of AI. Performing machine learning on edge devices like connected sensors and cameras can help businesses do everything from detect anomalies faster to efficiently predict maintenance. But optimizing machine learning models to run on the edge can be challenging because these devices often grapple with latency and unreliable connectivity.