|Google big machine learning, AI push by adding GPUs.....................................................................|
"It will be able to run more efficiently thanks to the addition of GPUs to the CPUs."
Bit intensity....on steroids.
Google is making a big machine learning and AI push in cloud services
Today, Diane Greene, the SVP for Google Cloud, announced a new push in Machine Learning and AI. There’s a new group under her division that will unify some of the disparate teams that had previously been doing machine learning work across Google’s cloud. Two women will take charge of the new team: Fei-Fei Li, who was director of AI at Stanford, and Jia Li, who was previously head of research at Snap, Inc. As Business Insider notes, Fei-Fei Li was one of the minds behind the Snapchat feature that lets you attach emoji to real-world objects in your snaps.The news came at the top of a slew of more announcements about the product roadmap for Google’s cloud services and how they’re expanding their use of machine learning. The announcements were all aimed at showing how Google’s cloud services include more than just renting time on a server — that it can provide services to its enterprise customers that are based on its machine learning algorithms. Those services include easier translation, computer vision, and even hiring.
For example, Google is talking up how it’s improving the infrastructure for Google Cloud. It will be able to run more efficiently thanks to the addition of GPUs to the CPUs its system already uses. Graphical processors are especially good at training machine learning systems more quickly. Google has also added some security layers to the GPU, something it claims isn’t necessarily common on other cloud platforms. So, Google says, there won’t be any data from a previous customer sitting in any of the GPU’s caches when the next customer starts spinning it up for their tasks. They’ll be available in 2017.
Google is also unifying its “cloud vision” API so the same system will be able to identify logos, landmarks, labels, faces, and text for OCR — making it simpler to implement. These systems will run on “Tensor Processing Units,” new hardware that’s optimized for Google’s TensorFlow platform. Google had previously unveiled the TPUs, but the new news today is that it’s cutting the price for “large scale deployments” by 80 percent.
Its natural language API is now globally available. It will be able to detect more “granular sentiment” in English, Spanish, and Japanese and also more “entity types” than it had in beta. Google’s natural language analysis will be able to handle morphology and syntax analysis. There’s also a new “premium translation” service.
Finally, Google is also introducing a new machine learning-based "Jobs API," which will apparently assist companies in doing massive "burst hiring" of hundreds of new employees. It allows computers to match up job openings with potential hires. Career Builder and Dice are signed up to use it, as is FedEx, Google says.