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Uncover Artificial

                                             Intelligence & Robotics







                    AI DOMAINS

                 We are all aware of the fact that every machine or organism is made of smaller parts that perform
                 specific types of tasks. Similarly, the AI system is also built from different smaller mechanisms
                 that help the AI work properly. These working mechanisms are the different components with
                 which the AI system can work. They are commonly called domains of AI. In this chapter, we are
                 going to learn about the different domains of AI.
                 Barr and Feigenbaum in 1981 defined AI as "the part of computer science concerned with designing
                 intelligent computer systems, that is, systems that exhibit characteristics we associate with intelligence
                 in human behaviour—understanding language, learning, reasoning, solving problems, and so on.”
                 Domains of AI

                 There are different approaches or domains in the field of artificial intelligence. There are various
                 methods through which we can develop artificially intelligent systems. Let us learn about these
                 domains.
                 Natural Language Processing (NLP)

                 This is a subfield of AI that helps in communication between
                 humans  and  computers  in  natural  language.  It  enables  a
                 computer to read and understand data by processing and
                 understanding human language.

                 This subfield of AI is used for a variety of tasks, such as email
                 filters. A lot of people receive a lot of emails that are useless. NLP checks the sender of the email
                 and categorises the mail as spam or junk. NLP also finds its use in the autocomplete and spell
                 check features of word processors. NLP is also quite useful in voice text messaging and virtual
                 assistants.
                 Data Science

                 Data science in AI refers to the process of collecting, analysing, and interpreting large sets of
                 data to enable AI systems to learn, make predictions, and improve their performance. It involves
                 using  various  techniques,  such  as  statistics,  mathematics,  and  computer  science,  to  extract
                 meaningful insights from data.
                 In  AI,  data  science  is  essential  because  AI  systems  need  data  to  learn.
                 For example, if you want an AI to recognise images of cats, you need to
                 provide it with a lot of pictures of cats. The AI uses data science techniques
                 to analyse these images, learn the patterns that define a cat, and then use
                 that knowledge to identify cats in new images.


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