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    This way, it can find hidden patterns or trends without anyone telling it exactly what to do. This
                      approach is useful because sometimes it’s hard to write clear rules for complicated or messy
                      data. The machine’s ability to discover patterns helps solve problems that rule-based systems

                      cannot handle easily.
                      Let  us  understand  the  concept  of  a  learning-based  AI approach  using  a  simple  example
                      of fruit  images.  In this  method,  the  AI model  is given  unlabelled data—in this  case,  various

                      fruits like  apples,  bananas, grapes  and pears—without  any names  or predefined  categories.
                      The machine does not know what each fruit is called or how it should be grouped. Instead of
                      following fixed rules, the AI analyses the visual features of the fruits such as shape, colour and

                      size  to  find  patterns.  It  then  learns from these  patterns and  clusters  similar  items  together.
                      For example, it groups all bananas together based on their long, curved shape and yellow colour
                      and clusters apples together based on their round shape, even if the colours vary. This process
                      is known as unsupervised learning, where the machine identifies categories or groups by itself
                      without human-provided labels.

                      The following image effectively demonstrates how a learning-based AI model can independently

                      observe, analyse and group data based on the features it detects.

                                                                                         Learning Approach

                                                                        Unlabelled Data

                                                                                             Model
                                                                       Used to Train Dataset

                                                 Unlabelled Data                                  Output

                                                    Output is clustered based on patterns observed by the machine:
                                          Left is based on roller stakes, Middle is based on Ice Skates and Right is based on Inline skates.

                                     Task                                                        Century   #Creativity
                                                                                                  21 st
                                                                                                  Skills  #Technology Literacy
                         Case: Substantial Electricity Bill (Continued…)

                         You begin designing a sensor and alarm system that detects movement in the room. If there is
                         no movement, the alarm will sound to remind someone to turn off the lights and fans.

                                     AI RoboGenius - VIII
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