his next generation of specialty chips for machine learning has announced, a subfield of artificial intelligence (artificial intelligence, AI). The cloud TPUs (tensor processing units) to allow faster and more efficient processing of machine learning algorithms. They should inspire not just Google’s own services, but are available through the Google compute engine for companies and independent developers.
“it is to us important, these advances benefit everyone – not just users of Google products”, CEO Sundar Pichai in a blog post insured. Great breakthroughs in complex social problems are expected, when scientists and engineers have more powerful tools for computing and research. “But today, there are still too many barriers that hinder the.”
could, for example, AI are accessible through the simplified creation of machine learning models called neural networks. Today, the design of a neural network is extremely time consuming and requires great expertise. The Internet Group will now show with AutoML as a new approach that neural networks can design themselves neural networks. He hopes that AutoML waiting with skills that today only a few graduates have. In three to five years to enable hundreds of thousands of developers to create neural networks for their specific requirements.
as is hardware based acceleration and machine learning to use processing unit in Google’s data centers tensor. Google revealed performance data of special chips only in the last month. Already the first generation of TPU was therefore a huge leap in performance for applications using trained neural networks.
related to artificial intelligence of optimized chips today behind answered queries and support services such as image search, Google photos and the Google cloud vision API. You should have allowed last year also substantial qualitative improvements of Google translate. Last but not least had helped in the victory by Google’s KI program AlphaGo against the world’s best players of the classic Asian board game go.
Google CEO Sundar Pichai in this context a new transition in computing – the shift from “Mobile first” looks to “AI first”. “As with previous changes that forces us to rethink our products for a world that allow for a more natural, more seamless interaction with technology from the ground up”, he writes. As an example he referring as well as the Smartphone that is operated using speech and answering to the camera “look” thanks to Google lens.
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