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September 28,5: Over the past four years, readers have doubtlessly noticed quantum leaps in the quality of a wide range of everyday technologies. Most obviously, the speech-recognition functions Life on your own our smartphones work much better than they used to. When we use a voice command to call our spouses, we reach them now.
Chinese search giant Baidu says customers have tripled their use of its speech interfaces in the past 18 months. Machine translation and other forms of language processing have also become far more convincing, with Google googlMicrosoft msftFacebook fband Baidu bidu unveiling new tricks every month.
Google Translate now renders spoken sentences in one language into spoken sentences in another for 32 pairs of languages, while offering text translations for tongues, including Cebuano, Igbo, and Zulu. Then there are the advances in image recognition.
The same four companies all have features that let you search or automatically organize collections of photos with no identifying tags.
You can ask to be shown, say, all the ones that have dogs in them, or snow, or even something fairly abstract like hugs. The companies all have prototypes in the works that generate sentence-long descriptions for the photos in seconds. To gather up dog pictures, the app must identify anything from a Chihuahua to a German shepherd and not be tripped up if the pup is upside down or partially obscured, at the right of the frame or the left, in fog or snow, sun or shade.
At the same time it needs to exclude wolves and cats. How is that possible? Click to enlarge the graphic. The advances in image recognition extend far beyond cool social apps.
Better image recognition is crucial to unleashing improvements in robotics, autonomous drones, and, of course, self-driving cars—a development so momentous that we made it a cover story in June. Ford fTesla tslaUber, Baidu, and Google parent Alphabet are all testing prototypes of self-piloting vehicles on public roads today.
The most remarkable thing about neural nets is that no human being has programmed a computer to perform any of the stunts described above. In fact, no human could. In short, such computers can now teach themselves.
The concept dates back to the s, and many of the key algorithmic breakthroughs occurred in the s and s. That dramatic progress has sparked a burst of activity.
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