Page 134 - Robotics and AI class 10
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Understanding the distinctions between these systems and their applicability in deterministic and probabilistic
        contexts is crucial in comprehending the capabilities and implications of advanced technologies in various
        domains such as robotics, self-driving cars, and machine learning.


        Automatic Systems
        Automatic systems perform their tasks according to the predefined rules and are deterministic in nature, meaning
        that there is a defined problem with the defined steps to solve it. Example is Robotic Arms used to make cars in
        the Automobile Industry in the assembly line.

        Autonomous Systems

        Autonomous systems are probabilistic in nature, meaning they do not have predefined tasks or defined steps
        to solve it, as they are trained to learn from their surroundings to act independently. Example is Self Driven Car.



                       Brainy Fact

              35% of Amazon’s revenue is generated using integrated recommendations into nearly every type
              of purchasing process.




                 Decision Making

        Have you faced a situation in life, where you have to choose one thing over the other? When you’re spoiled
        for choice in life, decision making becomes difficult. Whenever you are doing any kind of work you will have
        different choices and at that time you need to choose one over the other. What you choose will be based on
        many factors, like time frame, people involved, place, etc.
        Decision making is the process of comparing our different alternatives and coming to a conclusion on what
        exactly we want to do. It is a process of selection which is more satisfactory than other options. Our brain plays
        a very important role in making all types of decisions to deal with different problems in life.


        Human versus Machine Decision Making as Subjective and Objective
        The Decision Making in Humans is Subjective and is based on sentiments, feeling, belief, etc., which are defined
        by ethics, morals, and values followed by an individual. Due to the fact that each individual is different, the
        decision making on an issue is not the same by different individuals.
        The decision making in machines is defined by learning algorithms which are objective and are programmed to
        be based on consequence and factual information.

        Objectivity as per Humans is still having bias of subjectivity. Machines Objectivity is based on actual data with no
        subjectivity bias, in Decision Making. Machine learning is helping to bridge the gap between the two.


        How do You Make Decisions?
        We make decisions every day, starting from saying to doing, consciously or unconsciously. Everything we do is
        a result of our decisions. The choices that we get may be big or small, but there's no easy formula for the right
        decision. We form an opinion and choose the action based on reasons, our past experiences and availability of
        information. For any decision, the best possible way is to measure all the perspectives and then choose a course
        of action that seems reasonable.


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