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How do humans make decisions?
                  For example, imagine we are preparing a glass of lemonade, but we don’t know exactly how
                  much sugar to add.

                  Instead of following a strict rule, we taste the lemonade after adding some sugar, then adjust the
                  amount based on how sweet it is. Over time, we learn the best amount of sugar for our taste by
                  trying, observing, and adapting.

                  This process of learning from experience rather than following fixed rules is similar to how some
                  AI systems learn and improve.


                   Time of lemonade making               Amount of sugar added                Taste of lemonade

                   First time                      Very little sugar (quarter teaspoon) Not sweet enough


                   Second time                     Too much sugar (two teaspoons)          Too sweet

                   Third time                      Moderate sugar (one teaspoon)           Just the right sweetness

                   Fourth time                     Moderate sugar (one teaspoon)           Just the right sweetness




                                                                                               21 st  Century   #Media Literacy
                                                                                                   Skills
                            Video Session

                       Watch the video of "How does ARTIFICIAL INTELLIGENCE work?" at
                       the given link:

                       https://www.youtube.com/watch?v=fLcZRDiQyNY OR scan the QR code
                       and answer the following questions:

                       1.  How do characters in the video decide which direction to take?



                       2.  What do the different colours in the video represent?



                       3.  How does Rule-Based AI use predefined rules to reach a destination?








                  Learning-Based AI
                  A learning-based approach is when a machine learns by itself from the data it receives, instead

                  of following fixed rules made by a person. When the data is unlabelled or random, the machine
                  looks for similarities and groups similar data together.


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