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                                                                          AGENT
                                                           OrangeAI
                      If AI can only learn from data, how can it be sure it's making the right choice?

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                     HOW DOES AI LEARN?

                     Artificial Intelligence learns by collecting data, learning from it, making decisions and improving
                     over time through past experiences. Data can be classified as labelled data and unlabelled
                     data.

                       Labelled data: This is data that has been given a clear tag or label. Each piece of data has the
                        correct answer or category written alongside it.
                       Unlabelled data: This is data without any tags or labels. The data doesn't tell the AI what it is.

                        The AI has to figure out the patterns and similarities on its own.
                     Let’s break down each step of how AI learns:

                       Data collection: AI systems operate on vast datasets, making data collection crucial. They
                        gather information from various sources such as sensors, user activity, websites, cameras
                        and applications. This data can be unstructured, like images, speech or videos or structured,
                        consisting of numbers in a table. For example, a fitness app can collect data from your wearable
                        devices, such as a smartwatch, regarding the number of steps, heart rate and sleep data.

                       Learning from data: AI learns from the data provided to it. During the model training phase,
                        the AI model adjusts itself based on data to learn how to perform tasks and make predictions.
                        It also finds patterns in the data. For example, AI learns to recognise cats in photos by analysing
                        thousands of images labelled as “cat.”

                       Decision making: After learning from the data, the AI makes decisions or predictions. These
                        decisions  are based  on the  patterns  it  detected during the  training  phase.  For example,
                        a recommendation  system  decides  which film to  show you  next  based  on your  past
                        viewing habits.
                       Improvement: AI systems improve over time by receiving feedback and analysing results.

                        They retrain or update their models using new data or corrections. For example, a self-
                        driving car improves its driving decisions as it encounters more traffic situations and receives
                        updates.

                                       What is the next number in the sequence: 17, 35, 52, 69, __?

                                               a)  85                                             b)  90

                                               c)  86                                             d)  95

                                                                               Introduction to AI & Everyday Examples  21

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