Google bets on AI-as-a-Service with chip-and-cloud combo
Google has designed an artificial intelligence (AI) chip and supercomputer combination as part of its bid to lead the AI industry by developing both hardware and software for the technology. Called the Cloud Tensor Processing Unit (TPU), the chip quickly performs machine learning tasks and can be trained effectively, according to Sundar Pichai, CEO of Google. The company will also connect TPUs to create "AI-first data centres", which enable its machine learning tools to be accessed over the internet. Google will open 1,000 Cloud TPU systems to AI researchers willing to share details of their work.

The announcement reflects how rapidly artificial intelligence is transforming Google itself, and it is the surest sign yet that the company plans to lead the development of every relevant aspect of software and hardware.

Perhaps most importantly, for those working in machine learning at least, the new processor not only executes at blistering speed, it can also be trained incredibly efficiently. Called the Cloud Tensor Processing Unit, the chip is named after Google’s open-source TensorFlow machine-learning framework.

Training is a fundamental part of machine learning. To create an algorithm capable of recognizing hot dogs in images, for example, you would feed in thousands of examples of hot-dog images—along with not-hot-dog examples—until it learns to recognize the difference. But the calculations required to train a large model are so vastly complex that training might take days or weeks.

Pichai also announced the creation of machine-learning supercomputers, or Cloud TPU pods, based on clusters of Cloud TPUs wired together with high-speed data connections. And he said Google was creating the TensorFlow Research Cloud, consisting of thousands of TPUs accessible over the Internet.

“We are building what we think of as AI-first data centers,” Pichai said during his presentation. “Cloud TPUs are optimized for both training and inference. This lays the foundation for significant progress [in AI].”

Google will make 1,000 Cloud TPU systems available to artificial intelligence researchers willing to openly share details of their work.

Pichai also announced a number of AI research initiatives during his speech. These include an effort to develop algorithms capable of learning how to do the time-consuming work involved with fine-tuning other machine-learning algorithms. And he said Google was developing AI tools for medical image analysis, genomic analysis, and molecule discovery.

Speaking ahead of the announcements, Jeff Dean, a senior fellow at Google, said this offering might help advance AI. “Many top researchers don’t have access to as much computer power as they would like,” he noted.