Google has announced a limited preview for Cloud Vision API, a type of programming tool that could have significant implications for the future of enterprise applications, particularly in the area of productivity and collaboration.
Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API. It quickly classifies images into thousands of categories (e.g., "sailboat", "lion", "Eiffel Tower"), detects individual objects and faces within images, and finds and reads printed words contained within images. You can build metadata on your image catalog, moderate offensive content, or enable new marketing scenarios through image sentiment analysis. Analyze images stored anywhere, or integrate with your image storage on Google Cloud Storage.
Easily detect broad sets of objects in your images, from flowers, animals, or transportation to thousands of other object categories commonly found within images. Vision API improves over time as new concepts are introduced and accuracy is improved.
Vision API can analyze emotional facial attributes of people in your images, like joy, sorrow and anger. Combine this with object detection and product logo detection, so you can assess how people feel about your logo.
It's not clear when Cloud Vision API will become generally available. It's available at no charge during the early-access period, with pricing to be announced later.
More key details from Google.
An enterprise vision for Cloud Vision
Like any good idea in technology, Cloud Vision API is not the only player in the game. Microsoft has similar functionality with its Project Oxford API set, as does IBM with Watson AlchemyVision, noted Constellation Research VP and principal analyst Alan Lepofsky.
Some applications for Cloud Vision API are immediately obvious, such as for e-commerce sites and social media. But the tool, and tools like it, could have other significant implications, Lepofsky said.
"Google Cloud Vision API could lead to new ways for software to personalize and contextualize work," he said. "Using facial recognition could filter content relevant to the moment."
[On this matter, Google offered an important caveat: "Privacy is important to customers and to us -- this is not face recognition of an individual and no facial detection information is stored on Google servers."]
"Similarly, emotion detection could be used to filter content even further, for example by delaying the delivery of new emails at times where the receiver is showing stress," Lepofsky added.
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