AI from MIT teach robots to manipulate objects that they see in the first

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2018-09-10 17:45:06

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Even despite the fact that modern robots are very well know how to deal with different kinds of objects previously in their program need to lay the data about those objects. And if the robot gets something that he's not good – it leads the car to a screeching halt. However, a group of researchers from the Massachusetts Institute of technology (MIT) have created an algorithm that will teach robots to interact with objects with which they never before encountered.

According to Engadget, the development of responsible engineers from the Laboratory of computer science MIT. And their invention can make robots more useful not only in production, but also at home. At the moment, the main type of software, embedded in robots, allows you to perform a very limited set of commands: for example, to distinguish among objects (known in advance) that which is right in the moment or move from place to place pre-defined in the algorithm items.

New AI from MIT, called DON (Dense Object Nets), will allow robots to determine the structure and function of the artefact, which he sees at the moment. For example, running shoes need to put on the sole, and the mug easier to hold the handle and preferably not flip, as it can be filled with liquid. Based on incorporated in the program data, a neural network can self-improve, learn new things for themselves. Moreover, the AI remembers not only concrete objects but also their purpose. For example, if he's given the task to study some object, the AI will take some pictures and compare them with the existing. Then the virtual object is decomposed into "parts", consists of a frame of the object and its most important points. After that the object will be possible to interact. Moreover, if again to give the job to find the object among the same similar neural network not only immediately identify it, but also remember the whole class of similar objects, knowing that they can interact the same as the original.

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