Cloud AutoML - Custom Machine Learning Models

Google vows to simplify creation of custom machine learning models for developers

In 2017, it launched Google Cloud Machine Learning Engine to help machine learning developers build scalable ML models.

Cloud AutoML Vision is the first of these tools Google is planning to bring to market, and is geared towards speeding up the time it takes developers to create custom machine learning models for image recognition tasks.

The service provides a drag-and-drop interface that lets developers easily upload images, train and manage models, and then deploy those trained models directly on Google Cloud. Creating and maintaining a comprehensive set of product attributes is critical to providing our customers relevant product recommendations, accurate search results, and helpful product filters; however, manually creating product attributes is arduous and time-consuming.

Increased accuracy: Cloud AutoML Vision is built on Google's leading image recognition approaches, including transfer learning and neural architecture search technologies.

Cloud AutoML does this by offering users a simple graphical interface for training their own machine learning model.

Commenting on the development, Head of Research and Development, Cloud AI and ML Jia Li said Google Cloud's goal has been to lower the barrier of entry and make AI available to the largest possible community of developers, researchers, and businesses.

"We believe Cloud AutoML will make AI experts even more productive, advance new fields in AI and help less-skilled engineers build powerful AI systems they previously only dreamed of", the Google executives wrote.

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The platform addresses the lack of talent, knowledge and expertise in AI.

Disney and the Zoological Society of London (ZSL) are among the companies partnering Google to be early users of this technology.

This new service goes beyond Google's existing portfolio of cloud machine learning services, which are either aimed at assisting with the broadest number of applications, or helping existing machine learning practitioners streamline the process of plying their craft.

The services are created to build on the momentum the search giant claims to have seen to date with its push into the machine learning space. Retail and healthcare companies have been testing Cloud AutoML to automatically classify products or find very specific images, said senior director of artificial intelligence for Google Cloud AI.

Google is now developing several other AI-powered services within Cloud AutoML, according to Li and Li. In order to achieve this, ZSL has deployed a series of camera traps in the wild that take pictures of passing animals when triggered by heat or motion.

Sophie Maxwell, the conservation charity's technology lead, said Cloud AutoML is assisting with the society's research into the geographical spread of wildlife populations around the world, and how these are being affected by external factors, such as human-related impacts.

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