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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