presentation on Artificial Intelligence and its componenets.

1. COMPONENTS
Trinity Intl College
SUBMITTEDTO :LAL KRISHNA MALIK

2. AADITYA GUPTA PANKAJ YADAV SUMIT PANDEY
TEAM MEMBERS

3. C O M P O N E N T S

4. COMPONENTS OF AI
1.Search
This intelligence is used to search solution of particular problem like
possibilities of moves on chess playing game.
Searching is very important and needs to be very fast and must search with
accuracy, so Al based system is useful for particular problem oriented search
easily.
In these days, all organizations and institutions have huge database that
requires intelligence based efficient search what the user needs. There are so
many search engine companies; they are applying Al in searching techniques.

5. 2.Pattern Recognition
It is used to recognize some type of figures, images or audio sounds.
Its application is used for the authentication like face detection, iris
detection, voice recognition etc.
Pattern in any sense or any type which directly or indirectly presence in
the system, is also used for security purpose to authenticate and authorize,
because of its unique property, Al is intelligently manage and control the
recognition of any kind of pattern as per the requirement.
Now a days, to open and close any automated system there is partially or
fully Al based in built system along with sensor technique.

6. 3.Logic Generate
 As the name suggest, Al is intelligence with creating logic in different
problems.
Logic in terms of predicate basis or whatever, this system creates logic for
solving the any kind of related problems as per the AI related system and
software.
It is used for logic generate from the previous experience of compilation.
Like Cow is a mammal and gives birth (Hypothesis) If dog is a mammal
(Assumption) Then it must give birth (Conclusion)

7. 4.Common Sense and Reasoning
 The main goal of Al is to produce good reasoning power and produce
logic.
This reasoning power and logic made machines like human.
 It has also the capacity to think and do the given task using common
sense and reasoning for effective performance.
 It also has decision power to do the tasks in well manner for better result
automatically.

8. 5. Learning from Experience
 AI programming is built to learn from the experiences like human being.
Although learning are limited with comparison to the human beings and
also depends on the programming language used.
There are different tools embedded in Al based system for recognizing
and implementing the best practices.
 Heuristic Search is a kind of effective tools for achieving the result
intelligently.

9. 6. Genetic Programming
Al programs are used to solve relationship between humans.
As we see in genetically there is inheritance properties that can help the
future prediction.
 Al has the power of genetic programming capacity that can help for
future scenario result what will happen.
 Lisp (List Programming) is used to solve this type of problems

10. 7. Neural Network
Artificial intelligence technique that mimics the operation of the human
brain that refers to nerves and neurons, and comprises of densely
interconnected computer processors working simultaneously that means
parallel.
Neural networks are particularly effective for predicting events when the
networks have a large database of prior examples to draw on.
Strictly speaking, a neural network implies a non-digital computer, but
neural networks can be simulated on digital computers.

11. 8.Reasoning
The second major component of artificial intelligence is reasoning.
 While the concept of mental reasoning is something that has largely
been limited to the human mind for much of recorded history, much of the
development of artificial intelligence hinges on software programs that are
able to draw conclusions and inferences from a situation, without the need
for human interference.
Furthermore, these inferences are divided into two categories, inductive
and deductive reasoning. To this point, the use of inductive reasoning has
allowed computer programmers and software developers to create
products and systems that achieve consistent results when faced with a
particular problem or issue, whether this is in terms of a broad topic such
as automatic transcription and translation, or a more niche application
such as the cloud-based grammar and writing assistant Grammarly.