[0:00]Hello students. Today we are starting the first unit of Class 9th CBSE subject Artificial Intelligence, AI Reflection. If you see, this unit is divided into three parts. First is Session 1, Understanding AI. In this, we will see what is Artificial Intelligence, what are the different applications of AI, and what are the three domains of AI. Right. And the second session is about Project Cycle. In this session, we will see which stages we go through to develop an AI project. Right. And the third session is about Ethics & Morality. In this, we will talk about issues related to AI and what are the principles that we should follow while creating an AI model. Right? So let's get started. In this video, we will cover Session 1: Understanding AI. Right. So, if you see, AI stands for Artificial Intelligence. So, here artificial means that is man-made. Right? And intelligence means what human beings have. Human beings can communicate. They can understand the feelings of others, make decisions, improve themselves over time, and also predict the future. Right? But does that mean that other living beings, animals and birds, don't have intelligence? They also have intelligence. If I take an example, say, you have a dog at home, and when a stranger visits your home, you will see that the dog starts barking. This means that the dog also has intelligence. It can recognize the person, whether it is a stranger or a family member. Right? And if you see, it can also make decisions. It saw that this is a stranger, so it started barking. So, barking is its decision, that this stranger should not be allowed to enter this house. Right? So, this is its decision. And if you see, it is also communicating. It is barking and communicating to that stranger that you are not allowed to enter this house. Right? So, animals also have intelligence. And if we observe, if the same stranger visits your house repeatedly, then you will see that after two to three visits, the dog starts recognizing that person. Now, the third time, fourth time, when that person comes, your dog stops barking at that person. This means that dogs also improve. They learn over time that now this is not a stranger, this is a family member. Right? This means that all living beings can communicate, make decisions, improve themselves over time. Right? Even they can predict the future. If you have seen, whenever it is about to rain, some time before that, all the birds and animals start searching for hiding places for themselves. This means that animals and birds can also predict by looking at the weather conditions that it is about to rain, and then they make a decision that we have to hide. Right? So, here intelligence means what all living beings have. The ability to make decisions, the ability to communicate, all these abilities are present in all living beings. But human beings are more intelligent than other living beings. But if we talk about non-living things, there is no intelligence in them. If we take the same example, if you don't have a dog at home, if a stranger comes, then your main door or main gate, can it recognize that this person is a stranger or a family member? No, because non-living things do not have the ability to recognize. Right? In the same way, there are many non-living things around us that we use, like AC, refrigerator, mobile phones, cars, vehicles. All these are non-living things, and they don't have their own intelligence. You will see that when you enter your room, the AC that we use, can it analyze the room atmosphere, the room temperature,

[4:15]and increase or decrease its temperature without our intervention? No. If we talk about the refrigerator that we use, in which we store different items, vegetables, fruits, can the fridge check all the items on its own and tell us that this particular item, this particular vegetable, is out of stock, you should buy it and store it? No, because that is a non-living thing. It does not have its own intelligence. Right? All these devices, non-living things, do not have their own intelligence. But if intelligence is put inside all these devices, if your refrigerator analyzes all the items on its own and gives you a message that milk is out of stock or this particular fruit or vegetable is out of stock, it's finished, you should buy it. Then we won't have to check inside the fridge, so our life will be a little easier. Now, your AC, on its own, analyzes the room environment and decreases the room temperature without our intervention. So, this means that this AC is artificially intelligent. Say, your car, you sit in it and you tell it that you want to reach that destination. And it drives itself. As soon as a red light comes, it stops itself. Right? And it will choose the path on its own. You don't need to intervene. It takes its own decisions, recognizes the path. So, this means that that car is artificially intelligent. You all have heard about the Tesla car, which is a self-driving car. It makes its own decisions. So, that is also artificial intelligence, because the car itself has no intelligence. But we human beings have put that intelligence in that car. Right? Now that car becomes artificially intelligent. Right? In the same way, if you give instructions to a mobile phone, that just call that person who is in the contact list. So, the mobile phone, on your voice command only, calls that particular person itself. Right? So, you didn't dial that number. The mobile phone listened to you and dialed that number. So, this means that a non-living thing is able to listen to our words and understand them. Right? It doesn't have any intelligence that it can understand us. But now they are understanding our language.

[6:45]So, this is Artificial Intelligence. Now, if we say what is Artificial Intelligence, we can say that the intelligence that human beings have, like making decisions, recognizing persons, understanding language, predicting future, learning on its own, this intelligence, when it also comes inside a machine. That is, a machine also starts behaving like a human. Now, that machine becomes artificially intelligent. Right? I hope you have understood what is artificial intelligence. Now let's see some applications of AI. Now we can see we are surrounded by AI technology.

[7:29]All the devices we are using nowadays, all those devices are empowered by AI technology. If we see the smartphones that we use the most, you see the face lock system in them, this is also possible because of AI. Initially, you feed your face features once into the smartphone, then next time whenever you unlock the smartphone, it can recognize your face.

[7:53]Right? It can analyze your facial features and decide whether to unlock the phone or not. Right? And if we talk about smart assistants, Amazon Alexa, Apple Siri, Google Assistant, all these are voice assistants that work on our voice commands.

[8:14]Like, 'How is the weather?', 'Play some music?', Right? So, all these devices are able to understand and analyze these types of voice commands, our language. Right? They are able to understand all of them and make decisions on them. That is possible because of AI. And if we see in the banking sector or finance companies, in these sectors, there is a risk of fraud and financial loss. So, all these sectors use AI technology to detect all these frauds and risks. For example, say, usually a user's transactions are in Delhi or the surrounding area of Delhi. Now, whenever there is such a transaction that happens from some other location or there is a foreign transaction, in that case, AI technology treats this as a suspicious behavior and sends an alert message to the user. Right? Now here the user can decide whether to block this transaction or not. Right? Now, if you see, whenever there are loan applications in finance companies, it is a big risk for the company to provide a loan to any customer. Right? So, here companies use AI technology to analyze the past expenditure behavior of that customer, where and how much he spends, what is his profile, where does he work, if he has taken any other loan, whether he has returned it or not. Right? So, by analyzing all these factors, AI technology can tell how much risk is involved in giving a loan to this customer. Right? So, in this way, AI technology works here. And if we talk about the medical field, if we see medical imaging, MRI scan, CT scan, ultrasound, all these images and videos,

[10:07]AI technology analyzes them and can detect which part has which disease or which infection. Right? And it can help doctors. And also we have AI applications that will convert the 2D images into 3D images, so that doctors can get more details about the patient's health. Right? And if we talk about the entertainment field, we have seen that all the recommendations we get on Spotify, Netflix, YouTube, so here also AI technology is used. Right? So, all these applications, YouTube, Netflix, Spotify, use AI technology to find out the user's likes and dislikes, and then give recommendations to the user according to their likes. Right? And even on social media platforms, when you upload a post, you see that you automatically get recommendations about which friend to tag. Right? There also AI technology is used. And if we see the emails, inside the email, whatever email is received, it is filtered out and placed in which folder. Should it be placed in the spam folder, inbox folder, or any other folder? Right? This decision is also taken with the help of AI technology. And you all must have used the face filters. Right? When we capture our photo through the camera, we have filters through which we can transfer into another image, we can wear goggles, carry a lot of jewelry, whereas in reality, we are not wearing goggles or jewelry. Right? So, that thing is also possible because of AI. Right? So, these are the applications of AI. Now the question is, how do all these machines, or we can say AI devices, or the AI apps, how do they become intelligent? They become intelligent by using data and algorithm. So here data means it can be statistical data, images, videos, charts, audio, all kinds of data. If we see in these applications, the face lock system in smartphones, what is the data in it? Facial features. The facial features that are stored are also data. And the face through which you are trying to unlock, that is also data. Right? And if we talk about smart assistants, so the commands you are giving to smart assistants, play some music, tell me about the weather, this is also data, this is verbal data. Right? And if we see in finance and banking sectors, so the user's transactions, the customer's details, that is data. And if we see in the medical field, the images generated through MRI, CT scan, that is data. Right? The videos we capture, that is data. And if we talk in the recommendation system, the music you are listening to, the video you are watching on YouTube, the movies you watch on Netflix, all that is data. And if we see in the email filters, what is the data here? The email that is received, the text written inside that email, that is data. Right? Now we have understood what is data. Now, to analyze this data, to read this data, an algorithm is also developed. Right? You can understand the algorithm as a software. These are steps of instructions. So, if we see in smartphones, here the face lock system what does it do? It matches the facial features that are already fed and the face through which the mobile is being unlocked. If both the features match, then the phone will be unlocked. This means that such an algorithm is fed in the face lock, which compares two pictures, two visual images. Right? And if we talk about smart assistants, such an algorithm is used in smart assistants which can understand the language, can interpret it, can understand it. Right? And then makes decisions accordingly. And if we talk about the financial sector, such an algorithm is used in it which analyzes the previous data, transaction history, customer details, and extracts information from it. Right? In medical imaging, there is an algorithm to understand visual data. Right? So, all these AI devices and AI applications work on data, and an algorithm is fed to interpret and understand that data. Right? So, algorithm and data, using these two, our machine becomes intelligent. Clear? Now, let's talk about the game apps. Your book talks about three game applications. Your book also has their links. You can also see the links here. I would recommend that you go to all these links and play all these game applications once. I want to tell you the use of all these game apps, so you can understand the data and algorithm in these apps. If you see the first game app, this game app is Rock Paper Scissors. All of you must have played Rock Paper Scissors game. So, you all know its rules. So, if we play this game with this AI application, you will find that maybe you win the first two, three rounds. But you will observe that after the fourth time, mostly this AI application wins. Now, say, first time you chose rock, you won. Second time you chose scissors, you won. Then you chose paper, you won again. Then again you chose rock. But this time maybe this AI application wins. Again you chose scissors, again AI application wins. Then you chose paper, again AI application wins. So, if you see, from here this AI application has started winning. So, here this AI application, what is it doing? Whatever move you are choosing, whatever data you are giving to this application, it has seen a pattern inside that data. First rock, then scissors, then paper, rock, scissors and paper. Right? So, by recognizing this pattern, now it will make its next move. Right? So, we can see in this application, what is the data? Whatever move you select, that is data. Right? And here, what is the algorithm? The algorithm is to find patterns within all the data you have fed. Right? So, this AI application uses the algorithm to find patterns within this data, and then it will make the next move. Right? If we talk about the Semantris application, if you play in this application, you will see this type of screen. Here you will get a highlighted word. You have to remove this word from this plate. You have to move this word down. So, for that, you have to type a text here. If this text is related to this word, then this word will be removed from this plate. Right? It will reach the last. Otherwise, you will lose and you will get to type the next text. Right? If you see, this game app understands the meaning of both these words and checks whether these two words are related to each other or not. In this game app, what is the data? The text you type, that is data. And what is the algorithm? The algorithm used in it understands the meaning of the words used in human language and interprets the relationship between two words. Right? So, if you see, here is a pillow. So, if you have written sleep, then we know that this pillow is used for sleep. If you write bedsheet here, then also it can understand that pillow is used with bedsheet. If you type bed, then also it can understand that pillow is used on bed. Right? But if you wrote a different word, say, you typed pen here. Now, this application now understands the meaning of this pillow and pen. It can recognize that these two are not related to each other. Right?

[18:44]Now, here this time you will lose this game. Right? So, in this, such an algorithm is used which can understand the meaning of the words used in human language and interpret how two words are related to each other. Right?

[19:56]So, this is for understanding the language. And this application is recognizing the visual picture. Now, these three AI applications are representing different domains of AI. If you see, there are three domains of AI: Data Science, NLP (Natural Language Programming), and Computer Vision. Now, Data Science is that field of AI in which machines are taught to analyze data, interpret it, and extract some useful information from it. Right? For example, all the recommendations you get on social media sites, on YouTube, on Netflix, on Spotify. Right? So, all the AI used for recommendations, all that AI technology works on Data Science. So, whatever music and videos you watch, all that is data. All this data goes to all these applications. The AI technology used there, that technology is trained in analyzing the data. So, whenever you do online shopping, whenever you shop for a particular product, you must have seen that the ads of the same product start appearing on your system, on your mobile. So, all the advertising companies also use AI technology. All that AI technology is trained in analyzing the data. So, whatever data you give in different shopping sites or applications, that data is analyzed, interpreted, and then based on that, according to your likes and dislikes, you get ads and recommendations. Clear? And the second domain is NLP, which works on human language. In which we teach machines to understand human language. Right? How to interpret it and how to respond in that language. Right? If we see the voice assistants, all the voice assistants, like Google Assistants, Alexa, Siri, all of them work on our commands. Right? So, in all these devices, such algorithms have been put which can understand human language, can interpret them. Right? They can respond accordingly. And if we see, when you send a message on WhatsApp, whenever you chat, you must have seen that whatever type of chatting you do, you automatically get recommendations to complete that sentence, that word. Here also you are getting recommendations by understanding the meaning of that text. So, here the AI technology, that is trained in understanding the language. Right? If we talk about email filters, in email filters, the email that is received, whether it should be put in the spam folder, inbox, or other folder. That is also decided by AI technology. But the AI technology that decides, that AI technology, the algorithm used in it, or we can say that algorithm can understand human language. Or we can say that here AI technology has been trained to understand natural language, to interpret it. Right? Now, if we see the third domain, that is about computer vision. Right? Now, in this domain, we teach machines to recognize images and videos, to analyze and interpret them. Right? That is, machines are trained to understand images and videos. Right? To interpret them. Right? So, whatever face lock system, face filters, in medical field also, in medical imaging field, in all these fields, wherever AI technology is working with videos and images, the AI used there, that comes under this computer vision. Right? So, these are the three domains. Now, let's say, we have to develop such an algorithm in which the machine can understand videos and pictures, can interpret them. So, for that, we will study the computer vision field. So, in this field, we learn to develop such algorithms with which machines can understand images, understand, analyze them. Now, say you want to develop such an algorithm in which AI can understand language, can work on human language. So, we will study the NLP field. Because in this field we will see how we teach machines to understand a language. When we understand it, then we can develop a new algorithm related to it. Right? In the same way, when you study under Data Science, then you will understand how we teach machines to find patterns within data. Then you can develop such algorithms in which you can identify patterns. Right? I hope you have understood these three domains of AI and what AI is and what are the applications of AI.

[25:07]So, in the next video, we will discuss the different stages of the project cycle. Until then, take care and like and subscribe the channel.