Complete Introduction to Artificial Intelligence: Concepts, History, Applications, and Risks

Hello everyone, this is Rishali and welcome back to my YouTube channel CS and IT tutorials by Rashali.

In today's session, we will discuss complete introduction of artificial intelligence.

This video will be helpful for your university exam plus interview purpose. Let's start the session.

So previously we have already discussed all the subjects in detail with practical demo solve examples, real life

examples and important question bank. I have attached playlist of this subject in below description box. Please share

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Now in today's session we will discuss all this topic which include introduction to AI their real life

examples foundation and history of AI benefits and risk of AI then intelligent agent structure then agent types of

environment rationality and rational agent at the end we will discuss some important question back. Now let's see

all these points one by one. First question is what exactly artificial intelligence? As we know

artificial intelligence is branch of computer science where machine can think, learn and make decision like

human. So basically artificial intelligence is about to teach computers act smartly.

Now there are some AI simulations because AI is work like a human intelligence.

As we know nowadays billions of data have generated on daily basis. So this artificial intelligence learn from data.

They also try to solve multiple problems in industry, social problems, customer requirements, everything they try to

solve fastly, accurately and efficiently. Again as per the data artificial

intelligence make a decision. They train the model. They try to make decision on particular project. Again they

understand human language like chat GPT Google Germany copilot they understand the human language and as per that

language they give the answers again they recognize multiple images. So nowadays everywhere artificial

intelligence have used. So the question is why AI is important? See first and most important reason is automates

repetative task. They make every task more fastly and accurately. They reduce human efforts in that particular task.

Again they improve decision making process. They take a decision on large amount of data like there are social

media application, banking application, gaming application or multiple apps are there and within second multiple data

have generated right. So AI they improve the decision making process. They take a decision on this data which data is

structured, which data is unstructured or which data is accurate, which data is fraud. They make a decision according to

the data. Again, they save time and cost because they perform every task fastly and accurately.

Unlike human, they work 24 by7. They doesn't tired. They are available 24 by7 for your query.

And also again they handle large data efficiently because this thing are not possible manually.

And that's why artificial intelligence is one of the powerful tool in each and every organization, each and every

department in every industry. So this is artificial intelligence. Now the next one is real life

applications of AI. I think we all are familiar with this application. The first one is a virtual assistants like

Siri, Google Assistant, Alexa. So these all applications have used AI powered tools. They work like a human

intelligence. They can set reminders. They can play music. Also answer your queries. Also handle all home devices.

So they work like a human intelligence. Next one is recommendation system. Have you ever wondered about how Netflix

shows the movie that you might like? also Netflix or Amazon they recommended the products that you are interested in

right so this recommendation system also done by artificial intelligence they study all human behavior they study

searching of human queries and as per that they recommended you that you are interested it in this is called as

recommendation system next one is self-driving car like Tesla so they use complete artificial intelligence system.

There are multiple embedded devices have used like sensors, cameras. So they track all the obstacles. They track

about the uh traffic signals. So they handle complete driving safely and accurately.

Next one is face recognization like smartphones security system. So they recognize a particular person as per

their features as per their facial expressions. So voice recognization system is a more secured way in any

applications or devices. Next one is chatboards. Like we all are familiar with chat GPT copilot Gemini

right in daily life we are used all this chatboard. So this chatboard gives you all the answers of your queries

accurately as per your prompt. Right? Also they can help you for learning purpose, coding purpose and also writing

purpose. So these are the applications of artificial intelligence. They try to work like human intelligence and gives

you result more accurately, fastly and efficiently. Now the next topic is foundation of AI.

So basically the result of artificial intelligence is combination of computer science, mathematics, psychology, logic,

linguistic and engineering. So combination of all those thing is called as artificial intelligence.

Now the first and most important foundation of AI is computer science. In computer science, we can learn multiple

algorithms, different data structures, different programming techniques, also database connectivity. So this is the

base of artificial intelligence where we can develop intelligence system. They behave like a human, right? Next

foundation is mathematics. So artificial intelligence heavily used maths concept like linear algebra, probability,

statistics, calculus or optimization. So these are the base of artificial intelligence. By understanding this

mathematical formula, artificial intelligence process the data and make prediction accordingly. And due to

mathematical formulas, they improve the performance. That's why maths is the core part of artificial intelligence.

Next thing is psychology. So here artificial intelligence learn about the human about human behavior. Here

artificial intelligence can learn, think, solve problems, remember or recall information like a human.

Basically they understand the human behavior and try to work like a human. and also they perform every operation

more fastly and efficiently as compared to human. So study of human intelligence which is called as psychology.

Again next one is most important the logic. Here artificial intelligence based on the logic of particular product

particular application. Here they can learn about reasoning, decision making power and rulebased system. And due to

logic every product can be developed according the rule, according the structured choice.

And the last one is a linguistic. So again this is also most important like we are using chat GPT giny copilot. So

everyone process or understand the customer queries, user queries in their own language, right? So speech

recognization purpose, language translation purpose or to solve multiple queries of users. For that purpose,

linguistic is again one of the most important department. So these all are the foundation of artificial

intelligence. Artificial intelligence result is based on all these departments.

Now let's understand history of AI. So artificial intelligence this particular topic first time introduced in 1950.

The scientist was Alan Turing. They proposed two types of question. First question they check that if a machine is

think like a human or machine work like a human and another question is if human cannot compare between machine and human

conversion. So at that time machine got more intelligence right. So this thing have first time proposed in 1950.

Then in 1956 there was first time artificial intelligence research conference was organized called as

dartmouth conference. Multiple researchers from worldwide they participated in this conference and they

discuss on artificial intelligence topic. So here actually called as birth of artificial intelligence.

Their researchers believed that machine would also work like a human intelligence.

All the machine can work fastly and efficiently as compared to human. So this is called birth of artificial

intelligence. Now after that between 1974 to 1980 this era is called as first AI winter. So in

conference artificial intelligence this topic was introduced but at that particular time all the computers all

the machines are very slow expensive right and also they did not get the result as per the expectation.

So for this particular reason AI research funding was reduced that artificial intelligence concept they did

not get any funding or anything. So this is called first AI winter problem. Now in 1980 there are some expert systems

have generated. There are multiple AI programmers or developers are there. They try to build

any small applications related to the calculations related to the uh hospital care system like diagnosis system. They

try to build some small application. they are solving a particular issue or particular social problems. So this is

called as expert system. They make a system who are taking a decision as like a human.

Now after that in 1987 to 1993 this era called as second AI winter. So experts try to make more intelligent

system. They try to solve problems but these all systems are more costly and very difficult to maintain and that's

the reason artificial intelligence again lost funding here due to more expensive and costly processors.

Now in 1997 so this is a history in artificial intelligence field. So uh there is a IBM

computer called as deep blue. So this IBM computer defected Gary. He's a world chess champion. So first time in history

a computer defected a particular human. So at that time everyone analyzed like artificial intelligence having more

logical thinking as compared to human. So this system show that AI can beat human in complex logical games. So this

thing first time ever happened in history that any system beat human. Now in 2012 the first breakthrough for

artificial intelligence is deep learning concept. So in deep learning there are multiple

types of neural networks like artificial neural networks, convolution neural networks. So this neuron they work like

a brain of artificial intelligence and in 2012 big data have generated like WhatsApp applications are there then

banking applications are there. So these applications try to generate millions of data in this particular era. So to

handle all this big data this neuron can process it. Neuron can process all the data and make decision accordingly.

Again in 2012 there are powerful GPUs, powerful computer chips are there. They try to solve all the operations more

fastly and accurately. So this is a main breakthrough for artificial intelligence field. Now in

2016, so here Google launched their first program called Alpha Go. So go again uh harder or advanced version of

chess. So here Lee Sel is worldwide go championship. So at that time AI defected this world

champion in go competition. Again this particular game having more complex move as compared to chess. Still

system have won over the human. So again this is a major milestone for artificial intelligence

and now from 2020 to present we all know that this is the era of gender to AI agentic AI. So now artificial

intelligence can generate multiple text images and also code. We are using different

chatbot applications than self-driving card in every domain like education, healthcare, banking, every sector

artificial intelligence have used. So this is the history of artificial intelligence.

Now let's understand benefits of AI. One of the most important benefit is automation. So AI can perform every

repetitive task automatically. They reduce the human efforts. Let's take example of chatbot. Chatbot are 24 by7

available to you, right? You can search multiple queries and chatboard gives you an answer within a second. So this is

called as automation. The next one is accuracy. Again they reduce the human errors. They try to

solve problems more fastly and intelligently as compared to human. That's why this particular AI field used

in healthare system as we know in healthcare having the crucial data. So artificial intelligence try to detect a

tumor's image or again any particular disages image as per the symptoms as per the patient history.

Next one is speed like they process every data very quickly fastly and again one of the main reason is artificial

intelligence used in bank management system or in uh ethical hacking or fraud detection purpose they try to capture

everything more fastly and accurately. Next one again it available 24 by7 they uh they didn't like a human they didn't

want any break right they try to solve or available for customer all the time like uh virtual assistants are there

like Google assistant Alexa is there right they again try to solve all the uh home issues right they handle all the

home devices next one is personalization so they provide customized

recommendation So every user's interest are different right? So as per their interest they

provide the recommendation for movie on Netflix then for products on Amazon, Flipkart right? So this is called

personalization. Then decision making purpose again there is a large amount of data is there. So

artificial intelligence can be used for decision making purpose. they make a decision on particular data like loan

approval system in bank management. So as per the particular criteria as per the customer requirement they provide

the loan approval process. Then also there is a innovations are there because they enables new technologies day by

day. So first there is artificial intelligence then generative AI and now agentic AI is there. So innovations are

there. So these are the benefits of artificial intelligence. Now what is the risk of artificial

intelligence? As we know coins has two side. One is for benefits another one is a risk. So first and most important risk

nowadays it job displacement like artificial intelligence try to uh solve or try to do all the work automatically.

So this automation may replace human jobs like uh robots replacing factory workers right? Then uh privacy issues

are there. Nowadays everything are online right. So your username, password, banking credentials, then OTP

everything was come from online. So AI collects and analyze all personal data for example face recognization system

there. Right? Then a bias and discrimination. So sometimes artificial intelligence may give bias algorithm.

Assume that sometimes a particular machine not train properly and this particular thing that affect multiple

users. Right? Then security threats are there. Uh sometimes AI can be misused. Right? On Instagram there are multiple

deep fake videos are there. So that can be misuse of artificial intelligence. Then uh dependence on technology. So

human can fully dependent on artificial intelligence for just 10 + 20 purpose also they can use calculator right. So

human are completely rely on artificial intelligence like uh example of Google uh GPS navigation system. So user

doesn't remind any route of one location to another location. They are directly use uh GPS. Right? Then a lack of human

judgment. So artificial intelligence having lack of emotions and ethics. Right? So wrong automation also affect

on multiple users. So these are the risk of artificial intelligence. Now next topic is about intelligent

agent and this is a architecture of intelligent agent. For your exam point of view this is one of the most

important question. So in intelligent agent there are total four components. environment, agent, sensors andectors.

Now let's discuss every components in detail. Now first one is environment. So

basically environment is outside of agent. Let's take a example of self-driving car. So self-driving car is

agent and environment is road. Self-driving car is work on road right next GPT. We all are using chat GPT. So

chat GPT is the agent and environment is internet, right? So environment is always outside the agent.

Now next one is sensor. See here sensor is connected to connected to the environment. So basically sensors is a

hardware part. They collect all the information from the environment and this process is called as per

example in self-driving car. So this agent is self-driving car. So this sensor detect information from the

environment. For example, traffic signal is on. So sensor detect this information and provide this information to

theectors andectors actually perform the action they apply the brake right. So basically

sensors fetch information from the environment. So for that purpose they use hardware devices like cameras,

microphones, keyboard input or other. Got it? Now next is processing.

Sensor pass all the data to theectors for performing the action and this process is called as processing.

Let's take example sensor phase the data like traffic signal is on. So they pass this data to theectors. So this process

is called as processing. Now there is aectors. Soectors also called as actuators where

actually action is performed. For example, sensors again send the information that a particular uh they

want to turn left like car want to turn left side. Soectors actually perform the action. So for that purpose they use

wheels, steering, speaker, other robot arms. So this is called as intelligent agent. So again agent means your

self-driving car environment is road sensor fetch all the information from the environment whether turn left apply

brake or a traffic signals are on any obstacles are there they fetch all the information and send this information to

theectors andectors perform action accordingly. This is called as intelligent agent.

Now again in simple uh way uh I will tell you again what exactly intelligent agent see. Imagine a human. So human is

a agent. So their eyes work like a sensors. Brain are processing the data and hands or legs actually perform the

action right and surrounding are called as environment. So this is a basic example of this. See here when you see

the rain eyes detect the rain right brain decide and hands open the umbrella. So this is exactly how

intelligent agents have work. So let's prepare this diagram completely for your exam point of view purpose.

Now again uh next topic is agent and environment. So I will again explain this concept in simple language. So

agent can perform three operations perceive, acts and work. How? See assume that there are a human agent. Okay. So

their sensors are eyes and ears and actuators actually they perform the action that hands or legs. Right? Then

suppose agent is robot. So sensors are camera and other hardware parts and actuators are wheels and arms.

Another example suppose self-driving car is agent. So their sensors are radar and camera and actuators are steering and

brakes. Another example suppose agent is like a chat GPT. So sensors are text input and actuators are text response.

So this is a concept of agent, sensors and actuators. So basically pursue means they collect

information. Sensor collect information through environment. Acts means here actuator all always

perform action as per the collecting information and all these work combinely like a

artificial intelligence. Now next topic is environment. Again as per your exam point of view purpose this

is important topic. So as we discussed earlier environment means outside the agent where agent interacts with. So

these are the some again example like uh for self-driving car road is environment for a vacuum robot purpose house is

environment. Uh chess program purpose chessboard is environment chatboard purpose internet users are environment.

So these are the example of environment where your artificial intelligence system can work right now. Uh this

environments has some types uh this one. So in your exam they will ask about explain types of environment right. So

let discuss all these five types one by one. See here the first uh types of

environment is fully observable and partially observable. So fully observable means agent can understand

the complete environment. For example, chess game. So users chess programming everyone knows the complete chessboard

view. Right? This is called as fully observable. Next one is a partial observable. So

here agent cannot see everything. Some things are hide from the agent or some things are not display. Let's take

example of self-driving car in fog. So in fog a particular uh due to some environment or due to some f fog uh

traffic signals are not displaying properly. Then uh some ob obstacles are not displaying properly. Right? So this

is called as partially observable. Now next environment is deterministic and stoastic. So deterministic means

output is predictable. For example, calculator uh you can predict the output by using

mathematical or other calculations. Right? Stoastic means uh you can't predict the output that is randomness

involved. For example, stock market prediction. So stock market values are continuously changing right in SH market

in stock market these are not predictable. So this is called as stockistic environment.

Next one is episodic and sequential environment. So episodic means each action is independent.

Just take example of classification. Suppose emails are there. So as per the any keywords like offers, discount by

using that keywords you can check out the mail whether it is spam mail or not spam mail. But sequential means current

action affects the future. For example, chess game. While playing chess, your current move is effect on future moves.

Right? So this is called as sequential environment. Next one is static and dynamic

environment. So as we know static means environment does not change constant environment. For example, crossword

puzzles in particular environment cross word puzzles are there, right? But dynamic environment means environment

are continuously changes. For example, self-driving car uh environment are continuously changing, right?

And last one is discrete and continuous environment. So discrete environment means limited state, limited actions.

For example, chess. Chess having limited move, limited rules are there, right? And continuous environment means

infinite states like driving. So these all are the types of environment and your artificial intelligence system work

in this environment as per the requirement. Now next topic is rationality and

rational agent. So as we know uh for example self-driving car is agent and

self-driving car work on road. So road is a environment right. So what is rational agent? So rational agent choose

the best action for your environment. Again as per the available information by using sensor they collect the

information right and as per that information they take a decision. So they maximize the performance measures.

Let's understand with example. See same example is there self-driving car by Tesla. So here performance can be

measured by using safety, speed of car, uh required fuel efficiency. Right? So these are the some factors where

performance and success are evaluated. Right? Next one is if uh suppose a particular condition if pedatrician are

appears. So rational agent take a decision to apply brakes right. If particular obstacles are there rational

agent take a decision to apply brakes right. So there is a rational agent they take a accurate decision as per the

collected information. So this is called as percept of sequence. Again knowledge of environment is there and available

action plans. So available action means even if the car is late safety is priority right. So to move car to turn

left to avoid obstacles uh to monitor traffic signals. This all things are called as actions.

So this is a work of rationality agent to take a best action as per the available information. So this is called

as artificial intelligence. Now basically good artificial intelligence behavior means to

understand environment uh make a decision according the data take proper action and learn and improve yourself.

So these are the properties of good artificial intelligence. So this is all about. Now as for your

previous year question paper they have asked uh properties of agent task environment. So uh they have asked this

question for architecture purpose. Right? You have to draw the architecture of intelligent agent with a diagram is

there. Then define artificial intelligence and intelligent agent and their use for five marks. Then again

agent and its environment types of environment for six marks. applications of AI for three marks. Then again list

and explain risk and benefits of AI for five marks. Then define rationality and rational agent with example five marks.

So just uh remember the example of self-driving car. Right? So you can just explain this example with all features

and their diagrams. Then again note on history of AI with different applications for fomarks. So I'm

suggesting you prepare all these questions completely with diagram. So this is all about artificial

intelligence. Thank you. All the best for your exam and please subscribe the channel. Thank you.