7/06/2012 09:23:00 PM
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Google Builds Artificial Brain Which Can Recognize A Cat
The Google X laboratory has invented some pretty cool stuff: refrigerators that can order groceries when your food runs low, elevators that can perhaps reach outer space, self-driving cars. So it’s no surprise that their most recent design is the most advanced, highest functioning, most awesome invention ever… a computer that likes watching YouTube cats? Okay, it’s a bit more advanced than that. Several years ago, Google scientists began creating a neural network for machine learning. The technique Google X employed for this project is called the “deep learning,” a method defined by its massive scale. In layman’s terms, they connected 16,000 computer processors and let the network they created roam free on the Internet so as to simulate a human brain learning. Stanford University computer scientist Andrew Y. Ng, led the Google team in feeding the neural network 10 million random digital images from YouTube videos. The machine was not “supervised,” i.e. it was not told what a cat is or what features a cat has; it simply looked at the data randomly fed to it. Ng found that there was a small part of the computer’s “brain” that taught itself to recognize felines. “It basically invented the concept of a cat,” Google fellow Jeff Dean told the New York Times. So Google may have created a machine that can teach itself. But what Ng and his team have done is not as new as you may think. Over the years, as the scale of software simulations has grown, machine learning systems have advanced; last year, Microsoft scientists suggested that the “deep learning” technique could be used to build computer systems to understand human speech. This Google X machine is the cream of the crop—twice as accurate as any other machine before it. However, “it is worth noting that our network is still tiny compared to the human visual cortex,” the researchers wrote, “which is a million times larger in terms of the number of neurons and synapses.” After “viewing” random pictures from random YouTube videos, the neural network created a digital image of a cat based on its “memory” of the shapes it saw in the images. The cat the computer created is not any specific cat, but what the computer imagines to be a cat. Plato had his Forms, and now Google has its computer-generated cat image.
The Google X laboratory has invented some pretty cool stuff: refrigerators that can order groceries when your food runs low, elevators that can perhaps reach outer space, self-driving cars. So it’s no surprise that their most recent design is the most advanced, highest functioning, most awesome invention ever… a computer that likes watching YouTube cats? Okay, it’s a bit more advanced than that. Several years ago, Google scientists began creating a neural network for machine learning. The technique Google X employed for this project is called the “deep learning,” a method defined by its massive scale. In layman’s terms, they connected 16,000 computer processors and let the network they created roam free on the Internet so as to simulate a human brain learning. Stanford University computer scientist Andrew Y. Ng, led the Google team in feeding the neural network 10 million random digital images from YouTube videos. The machine was not “supervised,” i.e. it was not told what a cat is or what features a cat has; it simply looked at the data randomly fed to it. Ng found that there was a small part of the computer’s “brain” that taught itself to recognize felines. “It basically invented the concept of a cat,” Google fellow Jeff Dean told the New York Times. So Google may have created a machine that can teach itself. But what Ng and his team have done is not as new as you may think. Over the years, as the scale of software simulations has grown, machine learning systems have advanced; last year, Microsoft scientists suggested that the “deep learning” technique could be used to build computer systems to understand human speech. This Google X machine is the cream of the crop—twice as accurate as any other machine before it. However, “it is worth noting that our network is still tiny compared to the human visual cortex,” the researchers wrote, “which is a million times larger in terms of the number of neurons and synapses.” After “viewing” random pictures from random YouTube videos, the neural network created a digital image of a cat based on its “memory” of the shapes it saw in the images. The cat the computer created is not any specific cat, but what the computer imagines to be a cat. Plato had his Forms, and now Google has its computer-generated cat image.
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