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DOMAINS OF ARTIFICIAL INTELLIGENCE


                  The three domains of AI explain how it carries out complex tasks and what its capabilities are. Let
                  us discuss each of these and then interpret them together.


                  DATA

                  The starting point of every application is data and it
                  is the foundation  of artificial  intelligence.  Data is all
                  around us, be it a google search, a passport scan or
                  an online  shopping  history,  all of  this  contains  data
                  that is collected, analysed, and monetised. Data is not

                  just collected but also properly formatted and aligned
                  with the project requirements.

                  Examples of AI applications based on data:

                      Weather  prediction  models  using  AI need  data  such as temperature,  humidity  and all
                      underlying patterns that impact weather.

                      AI is used in the prediction of upcoming customer orders for the next season. This enables
                      retailers to plan the inventory and purchases that help them predict and control the cost.

                      The software that controls vehicles works with the control radar system, lane control feature,
                      accident avoidance features, cameras, GPS, etc. All these technologies are AI-based and rely
                      on data to function.

                      Companies like Google, Facebook and Amazon are ruling the world because they were the
                      first to build data sets. Amazon already knows what the customers are going to buy and all of
                      this has been possible because of predictive analytics and tons of customer data.


                  COMPUTER VISION

                  Computer vision is a subset of AI that helps machines see and extract meaning from pixels in
                  an image. It is a field of AI that enables computers to see, identify, and process images to derive
                  meaningful information from those images, videos, and other visual inputs. Computer vision is
                  important and linked to AI as AI-enabled systems must interpret what it sees just like human

                  vision and act accordingly.
                  The goal of computer vision is to train machines to see, process, and provide a useful result based

                  on the observations within a very short time. This can only be possible if lots of data is provided
                  to it which can be analysed over and over until it detects distinctions and ultimately recognises
                  images. For example, to train a machine to recognise tyres, it needs to study a lot of images of
                  tyres. and items related to it to learn to differentiate and recognise a tyre without fail.





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