Lec-3: What is Artificial Intelligence | Learn AI with Real Life Examples | Can Machine Think?? — Transcript

Full transcript

1. 0:00Hello friends, welcome to Gate Smashers
2. 0:02In today's video we are going to discuss
3. 0:04Introduction to Artificial Intelligence
4. 0:05And an introduction I don't want to give you those definitions
5. 0:09Which are already mentioned in the books
6. 0:10And we are studying from many years
7. 0:12Instead I want to make you understand with examples
8. 0:14Which you are using on daily basis
9. 0:16Show from where did artificial intelligence evolved?
10. 0:19During World War 2
11. 0:20When first computer was made
12. 0:22The basic purpose of that computer was to break the German communication
13. 0:25And to build this computer
14. 0:27There was a major role of Alan Turing
15. 0:29And in 1915 Alan Turing in a conference
16. 0:33Published a paper
17. 0:34Its heading was " Can machines think?"
18. 0:38That means can machines think?
19. 0:40And we are still finding the answer of this question
20. 0:43And actually what we want to do
21. 0:45We want to make such machines
22. 0:48Which can behave like humans
23. 0:50Can think like humans
24. 0:51And work like humans
25. 0:53Which means we want to make intelligent systems
26. 0:55And on this intelligent machines only our whole future depends
27. 1:01If I explain you with a simple example
28. 1:04We all use a smartphone
29. 1:06And there is a very big and major application in it
30. 1:10That is Google Assistant
31. 1:12Or Siri
32. 1:13Alexa
33. 1:14What we do in this
34. 1:15Any of our query
35. 1:17There is no need to type also
36. 1:18You can speak and put your query
37. 1:20And the query that you are speaking in your language
38. 1:22It is converting that
39. 1:24Through NLP, natural language processing
40. 1:26And then it is finding out its answer and giving
41. 1:29And Google is not handling data in gigabytes or terabytes
42. 1:34It is handling exabyte petabytes of data
43. 1:37So in such a huge amount of data
44. 1:39How is your query coming out within second or millisecond
45. 1:43What is it working behind it
46. 1:46Artificial intelligence algorithms are working
47. 1:49Other than that if I want to give another example over here
48. 1:52Of smart cars
49. 1:53Of smart cars or smart homes
50. 1:55Tesla company has made smart cars
51. 1:57Driverless
52. 1:58What is there in it
53. 1:59Use simply sit
54. 2:00In US already 50,000 cars are running
55. 2:03You sit in that enter the destination
56. 2:06It will drop you at your destination
57. 2:08How you have to give raise
58. 2:10How you have to apply break
59. 2:11If obstacle came then where it has to stop
60. 2:13How it has to stop
61. 2:14There is no need for you to tell anything
62. 2:16There is no need of any driver
63. 2:17It is automatically doing all these things on its end
64. 2:19How is it doing
65. 2:21As human being is driving the car
66. 2:23We think a lot of things in our mind while driving the car
67. 2:26We also keep consideration about future
68. 2:27After one or 2 kilometers we remember that maybe that bridge is not made
69. 2:33Or that road is not good
70. 2:34That thing is there in our mind
71. 2:35So in the same way we also want machine to keep all the things in its mind
72. 2:38It should learn, percept
73. 2:40And on that basis it should do decision making
74. 2:43Human being thinks somethings
75. 2:46Learns it
76. 2:47Takes a decision
77. 2:48That only we want, what the machines should do
78. 2:51We want to put decision making powers in machines
79. 2:54We are not saying that decision will be good or bad
80. 2:56We want that machines should take decisions by themselves
81. 2:59And artificial intelligence is working over here only
82. 3:02The barrier of intelligence between humans and robots
83. 3:06It is trying to break that
84. 3:08So behind that there are many learning algorithms
85. 3:11Searching, sorting algorithms are there
86. 3:13Reasoning algorithms are there
87. 3:15Which are working behind it
88. 3:16I want to give you one more simple example
89. 3:18Of Netflix
90. 3:19What we do in Netflix, or I want to give example of youtube
91. 3:22You get recommendations
92. 3:24On the basis of your behavior
93. 3:26How you are working on social media
94. 3:28What you like, what you dislike
95. 3:30On that basis you see advertisement
96. 3:33What is this thing
97. 3:34On backend artificial intelligence is analyzing you completely
98. 3:38And after analyzing they are also putting impact on your decision also
99. 3:43So this is artificial intelligence
100. 3:45And our whole future depends on AI only
101. 3:49I want to explain you with one more simple example
102. 3:51Let's say
103. 3:52One person is there
104. 3:54And that person wants to order pizza
105. 3:56He opened the application online
106. 3:58He entered customer Id in the application
107. 4:00And he is getting options of pizza
108. 4:02Over there vegetable pizza are there
109. 4:04Non-veg pizza are there
110. 4:05Such options are coming
111. 4:06In that he selected cheese burst
112. 4:08As he selected option of cheese burst
113. 4:10Immediately he got a warning over there
114. 4:12That your cholesterol value is high
115. 4:14Now how is this cholesterol value high?
116. 4:16Means how did it get that information
117. 4:19It is possible that through mobile number, this customer Id
118. 4:24Or it is possible that any other medical bill that he had paid
119. 4:26Or anyone had entered medical values online
120. 4:28So it is linking from there and automatically picking up the data
121. 4:31That person also does not know at present his cholesterol value is high or low
122. 4:35But along with that he got a message
123. 4:37That your cholesterol value is high
124. 4:39So you don't order this pizza
125. 4:41But what he did, he ignored it
126. 4:42And ordered the pizza
127. 4:44Again when he ordered pizza
128. 4:46And it is possible that it is showing that the cholesterol value is high
129. 4:50And along with that it is also showing value in bold handwriting
130. 4:53That this is your cholesterol value
131. 4:54Still you can ignore
132. 4:56Or you can order the pizza
133. 4:59If he ordered the pizza
134. 5:00Then now what will happen
135. 5:02It is possible that next time, third time
136. 5:03Our expert system
137. 5:05Which can be artificial intelligence
138. 5:07The option cheese burst
139. 5:09It will remove from his Id only
140. 5:11That means the cheese burst option is automatically deactivated from there
141. 5:15And this expert system
142. 5:17This decision making
143. 5:18How it is working? On basis of artificial intelligence
144. 5:21So our whole advertisement system
145. 5:24Our whole social media
146. 5:26All these on backend, which ever major companies name you take
147. 5:29These all companies are already working on artificial intelligence
148. 5:34And they have already made many such machines
149. 5:37Which completely work on human behavior
150. 5:40And over here in human behavior we talk about which terms
151. 5:43First of all reasoning
152. 5:45Reasoning means, we have to think something logical
153. 5:48Something sensible is to be thought
154. 5:49Like if I tell that you are giving any competitive exam
155. 5:52To qualify that competitive exam
156. 5:55You need more then 40% marks
157. 5:57And there is a person A
158. 5:59And that person a got 60% marks
159. 6:00So you took a logic from here you did a reasoning
160. 6:04That the person has qualified the test
161. 6:06This we have done it is a very easy funda for us
162. 6:09But we want to add this reasoning this logic into machine also
163. 6:13Then learning
164. 6:15Learning means as human being learn something
165. 6:19We learn things from our experience
166. 6:21And we use those things in future
167. 6:24So that the mistake it had done in past the reaction it had done in past
168. 6:28It will not repeat that in future
169. 6:30We want this thing only in the machines
170. 6:32That it should learn things
171. 6:34And it should learn and store
172. 6:36So that when it comes into the same situation next time
173. 6:38Then same reaction is not there
174. 6:40It can perform a bit better
175. 6:42Then problem solving
176. 6:44Obviously we are doing game playing
177. 6:47Already there are lot of game playing algorithms
178. 6:49Or we are doing computation
179. 6:51We are doing any mathematical computation
180. 6:52Then in that we are trying to solve problem
181. 6:56As our mind works
182. 6:58In that same way also want machines also to think on their end
183. 7:01And on that basis it should do decision making
184. 7:04Then perception
185. 7:05What is the meaning of perception
186. 7:07Like human beings
187. 7:07What does human does from his senses, like eyes, ears, nose
188. 7:11Her percepts them and after percepting them
189. 7:14It takes a decision in mind on basis of that
190. 7:17This we want from machines also
191. 7:19That machines should percept
192. 7:21Like I had given example of Tesla company
193. 7:23Tesla is already working on a technique
194. 7:26If its car has percepted anything
195. 7:29That in future, lets say its car is going
196. 7:31And it saw a jam
197. 7:33It percepted that some jam is there
198. 7:35Then after percepting
199. 7:36It will make a decision
200. 7:38That the car which will come further
201. 7:41That will not go from that particular road
202. 7:42So it will automatically transmit this thing to everyone
203. 7:46This message
204. 7:47So over here what are we trying to say
205. 7:48That we percepted something
206. 7:50Machine percepted something
207. 7:51Now over there work is not done manually
208. 7:54That you should do this
209. 7:55Machine is taking decision by itself
210. 7:58On that basis it is doing decision making by itself
211. 8:01This is actually the whole concept of artificial intelligence
212. 8:04And if we talk from the point of view of research and development
213. 8:07Then artificial intelligence, machine learning, deep learning
214. 8:11All these topics are very important
215. 8:14At this time
216. 8:15So this is the basic definition of artificial intelligence
217. 8:18It is that we want to make such machine
218. 8:20Which should behave like human
219. 8:22It should work like human
220. 8:23So how can we bring that intelligence
221. 8:25On this only whole artificial intelligence depends
222. 8:28Thank you