AI News, Google’s AutoML lets you train custom machine learning models without having to code

Google’s AutoML lets you train custom machine learning models without having to code

Google today announced the alpha launch of AutoML Vision, a new service that helps developers — including those with no machine learning (ML) expertise — build custom image recognition models.

While Google plans to expand this custom ML model builder under the AutoML brand to other areas, the service for now only supports computer vision models, but you can expect the company to launch similar versions of AutoML for all the standard ML building blocks in its repertoire (think speech, translation, video, natural language recognition, etc.).

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.

The company says that Disney, for example, has used this system to make the search feature in its online store more robust because it can now find all the products that feature a likeness of Lightning McQueen and not just those where your favorite talking race car was tagged in the text description.

Google’s self-training AI turns coders into machine-learning masters

Building and optimizing a deep neural network algorithm normally requires a detailed understanding of the underlying math and code, as well as extensive practice tweaking the parameters of algorithms to get things just right.

The difficulty of developing AI systems has created a race to recruit talent, and it means that only big companies with deep pockets can usually afford to build their own bespoke AI algorithms.

That limits what they can do—for example, programmers will only be able to use the tools to recognize a limited range of objects or scenes that they have already been trained to recognize.

Joaquin Vanschoren, a professor at the Eindhoven Institute of Technology in the Netherlands who specializes in automated machine learning, says it’s still a relatively new research topic, though interest in the area has been heating up lately.

That’s only likely to get worse as programmers attempt to design AI systems that move beyond simple image classification and attempt to tackle ever broader tasks.

And more recently, two Google scientists used reinforcement learning—a technique inspired by the way animals learn through positive feedback—to automatically improve a deep-learning system.

Google’s AutoML Creates Machine Learning Models Without Programming Experience

Interest in machine learning has exploded in recent years as companies realize it has applications in photography, self-driving cars, games, and more.

Google has long offered pre-trained neural networks accessible via APIs that can perform certain tasks, but that’s only useful if you need exactly what that model does.

The gist of Cloud AutoML is that almost anyone can bring a catalog of images, import tags for the images, and create a functional machine learning model based on that.

AutoML won’t compete with the cutting edge, highly tuned AI systems an experienced engineer could build, but few businesses have the money or resources to support the development of completely custom machine learning models.

The vision part of AutoML is just the first part of several features planned for the product. Google did not mention cost, but it’s likely businesses will have to pay for API access to the models they create in AutoML. 

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