NTA UGC NET
Gate Smashers
In today 's video we are going to see Syllabus of artificial intelligence. We are discussing this
specially for NTA and NET exam. The syllabus if Artificial intelligence is mostly same only But
if we talk about NTA or NET exam Then they have already given syllabus of Artificial Syllabi on
their website. The first topic is approach to AI Approach to artificial intelligence I have added
this broad topics according to their syllabus only And if you also follow the book of Rich and
Knight Or of Soraj Kaushik Then in that also you will get the topics like this unit wise only So if
we talk about approach to. AI So this is the most important Why am I telling this most
important Because every time you. will get question from this unit And which is the topic The
first. topic is heuristic search Over here in heuristic. search we will talk about A * , AO * * , Best
first We talk specially about this algorithm After that we talk over here about game playing
This is the most important topic in the artificial intelligence 2nd most topic over here is Fuzzy
set I will this also 3 start Because you will get questions from this also every year And
questions are of same pattern only Either it is AO * or it is best first Or you'll get questions on
DFS and BFS. Then I want to give neural network 2 stars over here.
Star is that You do n't have to leave this topic and go in knowledge And along with that we
have reasoning In reasoning we have statistical reasoning and statistical reasoning. In NLP we
have syntactic and semantic In Natural Language Processing these 2 are main topics Cover
from these 2 topics only There is theory of them and questions come related to them only
And many times I want to tell you one more strategy over here. I have bought this video And if
you will start preparation according to this video Then definitely you will get a lot of help. And
you will also enjoy that you will come to know Which topic you have to do Which topics you
can ignore a bit. Thank you for your help
What is Artificial Intelligence | Learn AI with Real Life
Examples | Can Machine Think??
Gate Smashers
Gate Smashers is going to discuss Introduction to Artificial Intelligence. We want to make
such machines which can behave like humans Can think like humans And work like humans.
, On this intelligent machines only our whole future depends on intelligent systems. We are
still finding the answer of this question And actually what we want to do. We want to put
decision making powers in machines We want that machines should take decisions by
themselves And artificial intelligence is working over here only The barrier of intelligence
between humans and robots is trying to break that So behind that there are many learning
algorithms Searching, sorting algorithms are there Reasoning algorithms are working behind it
I want to give you one more simple example. Artificial intelligence is the basic definition of
artificial intelligence It is that we want to make such machine Which should behave like
human behavior. We want machines also to think on their end And on that basis it should do
decision making Then perception Then learning Learning means as human being learn
something We learn things from our experience And we use those things in future.
Artificial Intelligence should work like human It should work in a way that works like human So
how can we bring that intelligence to that intelligence? "Only whole artificial intelligence
depends on this only whole artificial AI depends Thank you" "It should work as human" "Only
one whole artificial intelligent depends on the intelligence of a human"
What is State Space Search | Introduction to Problem Solving
in Artificial Intelligence
Gate Smashers
Gate Smashers is going to discuss State space searching It is one of the major application of
artificial intelligence. Problem solving That is how to solve a particular problem And if we talk
about era of 1960-1970 At that time the major research that was done in artificial intelligence
That is done on problem solving And in which we talk related to game Like tic tac toe game is
there. In 8 puzzle problem that we have a board of 3 * 3, we have 9 spaces and 9 places In
which we have 8 tiles which are numbered. I have random tiles numberd 1,2,3,4,5,6,7,8 I have
numbered tiles And I have one empty space Now over here first of all I have to represent the
problem precisely That I have. I know that this is my start state Now I want goal state Where I
want to reach Otherwise you will keep on searching. You are starting to explore your
searching And these are different branches These different branches are getting formed. If we
keep the space on left side Then this will be formed over here like this If I do it on left then 5
will come here. If you move it left side then the next state That will be one of my resultant
state Then comes cost We measure it in cost What is the meaning of cost?
We do searching in 2 ways either we do it uninformed or blind search. In uninformed search
we use concept of heuristic due to which we try to solve the problem quickly In which we go
towards benefit towards local benefit So that my problem can get solved quickly Because
uninformed takes exponential time Because in uninformed B^d Time complexity is O ( b^d )