Google

Google just made it a lot easier to build your very own custom AI system.

A new service, called Cloud AutoML, uses several machine-learning tricks to automatically build and train a deep-learning algorithm that can recognize things in images.

The technology is limited for now, but it could be the start of something big. 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.

“We need to scale AI out to more people,” Fei-Fei Li, chief scientist at Google Cloud, said ahead of the launch today. Li estimates there are at most a few thousand people worldwide with the expertise needed to build the very best deep-learning models. “But there are an estimated 21 million developers worldwide today,” she says. “We want to reach out to them all, and make AI accessible to these developers.”

Cloud computing is one of the keys to making AI more accessible. Google, Amazon, Microsoft, and other companies are rushing to add machine-learning capabilities to their cloud platforms. Google Cloud already offers many such tools, but they use pretrained models. 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. A new generation of cloud-based machine-learning tools that can train themselves would make the technology far more versatile and easier to use.