The Google Brain network of New York Times fame is a nine-layer sandwich of autoencoders and other ingredients that learns to recognize cats from YouTube videos. At one billion connections, it was at the time the largest network ever learned. It’s no surprise that Andrew Ng, one of the project’s principals, is also one of the leading proponents of the idea that human intelligence boils down to a single algorithm, and all we need to do is figure it out. Ng, whose affability belies a fierce ambition, believes that stacked sparse autoencoders can take us closer to solving AI than anything that
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