The rise of artificial intelligence has made many industries feel the convenience brought by technology. Now many research teams and large enterprises are actively let AI robots carry out deep learning, but this kind of learning is mostly based on big data, if AI robot can Learning and perceiving through tactile feedback is even more "living". A few days ago, TechCrunch reported that a robot called "Baxter" is undergoing a tactile feedback training. It has only one task per day, that is, randomly grabbing items from the table, but its crawling speed is very slow and looks very clumsy. In this way, it carried out 50,000 grabs in a month, during which Baxter constantly adjusted the strength of the items and the accuracy of the movement. The development of Baxter is from the research team of Carnegie Mellon University in the United States. Recently, the team also published a paper on this research, which explains how to make AI robots enhance the recognition of objects through repeated contact with objects. . The team believes that this way of learning will be more helpful for AI robots to communicate with humans, and to create a name or file when discovering things that do not exist in the database. In addition, the research team assistant Dhiraj Gandhi used an experiment in the United Kingdom in the mid-1970s as an example. At the time, the researchers conducted cognitive experiments on two cats, one of whom lived as usual, in contact with the world, and the other cat. Only able to watch, not allowed to touch items, and finally only cats allowed to interact with the environment learn how to crawl, the only one that can be observed can not do the same. The method used on Baxter is: when you recognize a familiar item, a "smile" expression appears on the display and the item is grabbed into a suitable basket. If you are unfamiliar with the item, a "confused" expression will appear on the display. In this way, the AI ​​robot's perception of the unknown can be carried out more actively, rather than passively accepting some ready-made data. Once the AI ​​robot masters this skill, the future can be used in areas such as item sorting and entertainment interaction.
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