The next step in AI is to teach machines to think like us
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When you think about the "incredible" task, which can handle a computer, the first thing to come to mind of complex computations in a short time or analysis of massive volumes of data — something you will never be able to solve themselves. Or remember the go, the classic strategy game. The latest victory of AI became possible thanks to deep learning, which now opens up all possibilities for AI and the people that stand behind it.
But the simple everyday tasks that in their right mind can make even a child, apparently, undermine the functionality of the AI systems: such things as the definition of food that is on your plate, or identification of emotions on the face of another person. These easy tasks for humans was impossible. Up to this point.
Deep learning Methods gave the machine common sense. In the past programmers have written complex algorithms that were described everything down to the smallest detail. Such explicit and deterministic algorithm is appropriate when your goal is big awkward calculations. Deep learning AI exempt from such restrictions, allows the system to learn from their mistakes, to remember everything she learned to communicate with users for more information.
Revolution deep learning is mostly due to the fact that for learning big data becomes available. Baby human can learn what you need after a few attempts, but the car it will take much more time. Deep learning relies on access to vast amounts of data, because the machines working on the AI should base its choice on the probabilities and statistical significance. Mechanical replacement of intuition not yet invented.
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Advances in deep learning have significantly improved the capabilities of voice search: Google has replaced the Android speech system with a new system based on deep learning, and errors decreased to 25 percent overnight. Camera using deep neural networks can now read aloud and to understand the language. Facebook boasts that its potential in-depth training made the platform accessible to blind users, learning to describe the pictures.
In the coming years as large technology companies and many startups start to use deep learning to create new products and services, as well as for upgrading existing applications. New markets and businesses will grow and drive innovation of services and products. System deep learning will improve and become more affordable and easy to use. The simpler they will use, the more it will change our interaction with technology.
Aditya Singh, partner at Foundation Capital, believes that the development of the operating system, deep learning will lead to the democratization of deep learning and encourage the widespread introduction of practical AI. The result will be that people will be able to solve their immediate problems or something more substantial using deep learning. In this sense, the AI can be a mechanism for egalitarianism, allowing people of any class and status to change the world.
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