It is a traditional approach that deals with designing an
algorithm for solving complex real-world problems. In this approach, data is
fed to the machine and programmer states exactly how to perform the given

It follows a logical series of steps to teach the
conclusion. Conventional computers are also called von Neumann computers.
Environmental factors are not taken into consideration i.e., the problem will
be solved according to the predefined solution whatever may be the situation.

In this case, only one problem can be solved at a given
time. Conventional computing doesn’t observe or adapt based on the situations
and is incapable of making the decisions on its own. Solutions are not based on
rational thinking.

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It is a modern approach that involves learning and understanding
the problem, and the solve the specified task accordingly. Environmental
aspects are considered here.

Here, the machine observes and understands the problem, use
acquired knowledge to accomplish the specified task. It uses techniques of
search and pattern matching.

In this case, programmers design artificial intelligence
software to give the machine only the problem and not the steps or instructions
to accomplish the task.

Here a wide range of problems can be solved at a given time
in given domain. Intelligent computing has the ability to stimulate the human
behavior and apply cognitive thinking.


For tic-tac-toe game, in case of conventional computing,
programmer provides the instructions, applies brute force approach to check all
possible conditions while in intelligent computing, opponent’s actions are also
considered and then the decision is taken accordingly.

A humanoid Sophia uses AI to sense the environment, make
decisions on its own using rational and cognitive thinking. With conventional
computing alone, creating such an invention would have been impossible.


Turing test, developed by Alan Turing, determines the
intelligence of the machine, A machine is intelligent if it produces human
responses under specific conditions. A solution is said to be intelligent if it
delivers accurate results in minimum amount of time.


Learning agent is an intelligent agent that observes its
surroundings through senors and takes action accordingly (actuators). It learns
and uses the knowledge it acquired to achieve the goals. It consists of
learning and performance elements.

Utility agent allows rational decisions where there are
conflicting goals and we need to decide what is the best solution for the
specified problem.

e.g., while shopping utility agent can help in choosing
among alternative brands by trading off quality for price while learning agent
will analyze the shopping trends and use its knowledge to improve the business.


The solution which is chosen depends on the situation,
mainly smart solutions are preferred as the use reasoning, efficiency and
environmental aspects to accomplish the task.





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