Google's New AI System Could Be 'Machine Learning' Breakthrough
Whether you're trying to translate something into a different language, turn your spoken words into text or sift through thousands of saved photos for that one special snapshot, Google has built a "smarter" artificial intelligence system to help, company
representatives announced this week.
Google's new "TensorFlow" system is the backbone of many of the company's core functions, ranging from "Smart Reply," which suggests up to three responses to emails, to speech recognition functions in the Google app.
"TensorFlow is faster, smarter and more flexible than our old system, so it can be adapted much more easily to new products and research," Google representatives said in the company's blog post announcing the new system. [Super-Intelligent Machines: 7 Robotic Futures]
he tool is an exciting development for artificial-intelligence enthusiasts and researchers.
"TensorFlow is the first serious implementation of a framework for 'deep learning,' backed by both [a] very experienced and very capable team at Google," said Andrej Karpathy, a Ph.D. student at Stanford University who studies machine learning
.
Deep learning is a concept in artificial intelligence that means computers can learn more abstract concepts that humans traditionally perform better than computers do. For example, a human can recognize an image of the Taj Mahal without thinking much about it; people don't need to be told that it isn't an elephant or another monument. But computers have a lot of trouble with that kind of task — asking a computer to identify the Taj Mahal would require it to go through an entire library of images and hope it gets a match.
It gets even worse when you want a computer to recognize activity, said Aaron Courville, an associate professor of computer science at the University of Montreal. Humans can see in an instant that a person is walking down the street, and make assumptions about the person's destination or purpose. A computer, on the other hand, can only tell which direction the walker is going in, and that's about it — for now.
TensorFlow simplifies a lot of that research, Courville said, and allows researchers to build their machine learning systems more easily. "With TensorFlow, it's a set of tools, or a library, that allows you to construct these things and run them in an efficient
way."
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Whether you're trying to translate something into a different language, turn your spoken words into text or sift through thousands of saved photos for that one special snapshot, Google has built a "smarter" artificial intelligence system to help, company
representatives announced this week.Google's new "TensorFlow" system is the backbone of many of the company's core functions, ranging from "Smart Reply," which suggests up to three responses to emails, to speech recognition functions in the Google app.
"TensorFlow is faster, smarter and more flexible than our old system, so it can be adapted much more easily to new products and research," Google representatives said in the company's blog post announcing the new system. [Super-Intelligent Machines: 7 Robotic Futures]
he tool is an exciting development for artificial-intelligence enthusiasts and researchers.
"TensorFlow is the first serious implementation of a framework for 'deep learning,' backed by both [a] very experienced and very capable team at Google," said Andrej Karpathy, a Ph.D. student at Stanford University who studies machine learning
. Deep learning is a concept in artificial intelligence that means computers can learn more abstract concepts that humans traditionally perform better than computers do. For example, a human can recognize an image of the Taj Mahal without thinking much about it; people don't need to be told that it isn't an elephant or another monument. But computers have a lot of trouble with that kind of task — asking a computer to identify the Taj Mahal would require it to go through an entire library of images and hope it gets a match.
It gets even worse when you want a computer to recognize activity, said Aaron Courville, an associate professor of computer science at the University of Montreal. Humans can see in an instant that a person is walking down the street, and make assumptions about the person's destination or purpose. A computer, on the other hand, can only tell which direction the walker is going in, and that's about it — for now.
TensorFlow simplifies a lot of that research, Courville said, and allows researchers to build their machine learning systems more easily. "With TensorFlow, it's a set of tools, or a library, that allows you to construct these things and run them in an efficient
way."MORE AT SITE