Google launches Cloud AutoML to democratise AI


The gist of Cloud AutoML is that nearly anyone can bring a catalog of images, import tags for the images, and create a functional machine learning model based on that. "In 2017, we introduced Google Cloud Machine Learning Engine, to help developers with machine learning expertise easily build ML models that work on any type of data, of any size".

With Cloud AutoML, businesses will be able to create a simple machine learning model in minutes to pilot their AI-enabled application or build out a full production-ready model within a day, said Jia Li, head of R&D, Google Cloud AI. You typically need at least some programming to train a machine learning system, which rules it out for companies that can't justify a data scientist for the task.

Google has set out to change that by introducing today a new cloud toolkit called AutoML that provides a drag-and-drop interface for training AI models.

Google Cloud AI has launched other programs to help spread AI in the past year.

This should theoretically also apply to any future tools Google will add to AutoML.

The basic idea here, Google says, is to allow virtually anybody to bring their images, upload them (and import their tags or create them in the app) and then have Google's systems automatically create a customer machine learning model for them.

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Cloud AutoML helps tech professionals build custom machine learning (ML) models, using techniques like transfer learning and learning2learn, the post said.

"AI and machine learning is still a field with high barriers to entry and it requires expertise that (only) few companies can afford on their own", said Ms. Li, who is also the director of the Artificial Intelligence and Vision Labs at Stanford University. Early adopters of Cloud AutoML Vision include Disney, the Zoological Society of London, and the clothing retailer Urban Outfitters.

"We showed how modern machine learning services, i.e., APIs-including Vision, Speech, NLP, Translation and Dialogflow-could be built upon pre-trained models to bring unmatched scale and speed to business applications". AI building blocks for text, speech, video, vision can be provided by our machine learning APIs.

It was created in close partnership with Google Brain and other Google AI teams, with Google Cloud noting that several other Cloud AutoML products are already in development.

Those are some real-world implementations of Google's Cloud AutoML technology, which it launched globally on Wednesday (Jan 17). 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.

"The millions of images captured by these devices are then manually analysed and annotated with the relevant species such as elephants, lions and giraffes, etc, which is a labour-intensive and expensive process", Ms Maxwell said in the blog post.