Introduction to Artificial Intelligence

The intelligence shown by the machines in par with the natural intelligence of humans is called artificial intelligence. The computer program is made to learn, think and act according to human beings. So we can say that we are making machines smart. The best examples are speech recognition and image recognition. Different types of AI include reactive machines, limited memory, the theory of mind, and self-awareness. John McCarthy is called as the father of AI as he called the term first. The system can analyze and interpret data, learn from the data, and make conclusions from the data due to AI.

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What is Artificial Intelligence?

According to John McCarthy, the father of AI, “The science and engineering of making intelligent machines, especially intelligent computer programs, ” defines Artificial Intelligence.

As the name suggests, AI is imparting intelligence to the machines so that the machines operate like human beings. AI is that sector in computer science that emphasizes the creation of intelligent machines that work, operate, and react like human beings. AI is used in decision-making by machines considering real-time scenario. An Artificially Intelligent machine reads the real-time data, understands the business scenario, and reacts accordingly.

Some of the activities that the artificially intelligent machines are designed for are:

Speech recognition
Learning
Planning
Problem-solving

AI has now become a very important part of Information Technology. This branch aims to create machines that are intelligent. AI has highly technical and specialized research associated with it.

The biggest problems with AI include coding and programming computers for certain functions like:

Knowledge
Reasoning
Problem-solving
Perception
Learning
Planning
Ability to manipulate

The process of transforming a computer into a computer-controlled robot or designing software that thinks and reacts exactly the way a human being thinks is what AI is all about.

In order to use AI to develop intelligent systems, it is necessary that one understands how the human brain functions. How the brain thinks, learns, decides, and operates while solving a problem is to be studied thoroughly. Then, the result thus obtained must be applied to the software in order to develop smart and intelligent systems.

The core concept of AI research is Knowledge Engineering. Machines can only act, operate and react like human beings if they provide enough information relating to the business and the world. Hence, it is important that AI have access to all the information regarding the objects, categories, properties, and relations between all business use cases so that the machine can efficiently implement Knowledge Engineering. However, thearting the machines with common sense, decision making, reasoning, and problem-solving power is quite difficult and tedious.

Philosophy of Artificial Intelligence

The man has been using computer systems for a while now. While machines have always helped human beings, man always thought about exploring these slaves more and more. This curiosity led man to question, “Can a machine be made to think and operate as human beings?”

Hence, with the objective of making machines that operate and react like human beings, AI developed.

Goals of Artificial Intelligence

Given below are the goals mentioned:

To create intelligent & expert systems: The development began to make systems that exhibit intelligent behavior. The expected functions of these machines are learning, demonstrating, explaining, and advising its users.
To inculcate human intelligence into the machines: Creating systems and developing software that understands, thinks, learns, and behaves like humans.

What Contributes to Artificial Intelligence?

AI is essentially science, and technology – that is based on various disciplines. The areas of studies like Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering.

The main objective and a major challenge in AI is developing the computer functions associated with attributes such as human intelligence, which includes reasoning, learning, reacting, decision-making, and problem-solving.

One or multiple attributes from the ones mentioned above can be used to develop an intelligent machine.

Machine Learning is a core part and a subset of AI. Making machines learn without any kind of supervision is very difficult and hence requires the ability to understand the data, like identifying patterns in streams of inputs. This is very different from learning with supervision. Learning with supervision involves actions like classification and numerical regressions. Classification is the process of determining what category the object belongs to. The process of regression deals with obtaining a set of numerical inputs and thereby discovering functions that enable the generation of suitable outputs for the respective inputs.

Computational Learning Theory is a very well-defined branch of theoretical computer science that uses Mathematical Analysis which is done using Machine Learning Algorithms. The perception of the machine, reaction, and decision-making totally depends on the capability of the machine to use inputs from various sensors to deduce various aspects of the environment. For, eg. The computer vision analyses the visual inputs, and facial recognition, object recognition, and gesture recognition are the subsets of the overall analysis. Robotics is another major field that is somewhat related to AI. Various tasks handled by robots are navigation and object manipulation. The subproblems are localization, mapping, and motion planning.

Programming Without and With Artificial Intelligence

Given below is the basic programming of a system and how different they are when developed with and without the use of AI:

Without AI	With AI
The system can only solve specific problems and answer specific questions that are already fed in the system.	The system that is built using AI can be active in generic situations and uses the information, weighs options, and then make decisions.
Any modification or change in the program written or information can significantly change the structure of the application.	Whereas programs with AI can easily adapt to new changes and modifications by integrating highly independent pieces of information to access various data to make informed decisions. Hence modifying even a minute piece of information of the program would not affect its structure.
Opposing to what is expected, modifications are not as easy and quick. A minute change may affect the program adversely, thus, leading to malfunction.	On the contrary, making modifications in AI programs is very easy and quick. These programs are very adaptive and making changes do not affect the functioning of the program.

Challenges in Artificial Intelligence

There are two sides to every coin. AI also comes with its own challenges. Theoretically, this may seem simpler, buy in real-time, AI has certain challenges and knowledge, and the program has its unwelcome properties.

These includes:

Its volume is huge, more than what can be imagined.
The program and the guidelines are not at all well-organized or well-formatted. Hence, it becomes difficult to use it efficiently.
It keeps changing constantly. Hence, one has always to be updated.

What is Artificial Intelligence Technique?

In order to overcome these challenges, AI Technique is used.

It is a process to organize and efficiently use the knowledge so that:

The providers of the information should be able to perceive it.
Making changes to the data and the program should be easy and should be easily modified to correct errors.
Even though the program being inaccurate or incomplete, it should be useful in multiple scenarios.
Given that programs using AI are very complex, these AI techniques should elevate the speed of execution of these programs, thus, optimizing the efficiency.

Applications of Artificial Intelligence

We have seen that using AI has many advantages in programs where real-time data is to be used and manipulated. AI has been used and is dominant in various fields where reading, and manipulating real-time data is necessary,

Such as:

1. Gaming

Strategic games like Chess, Poker, and Tic Tac Toe require the assessment of real-time data. The machine should be able to think of various possible actions and should be able to weigh those options and make a decision based on heuristic knowledge. AI plays a crucial role in these strategic games.

2. Natural Language Processing

In order to make the program run efficiently, it is necessary that the machines the language of different users. The machine should be not only adaptive to various languages but also to various dialects and accents. AI is proven to be very useful in such use cases.

3. Expert Systems

The main function of an intelligent machine is decision making. These machines require software that accepts the information as input, understands it, weighs various options, and comes to a conclusion. These machines are used to impart reasoning to a given situation. Such software provides explanations and advice to the users to make informed decisions.

4. Vision Systems

Visual input is that form of information that is crucial and difficult to interpret. Hence a system integrated with Intelligence must read, understand, interpret and comprehend the visual inputs and make decisions based on this information.

Some Examples of these Applications

A drone, spying camera, or a spying airplane takes photographs, and videos, which are used to understand the map of the area or figure out spatial information.
Clinical expert systems use cameras inside the body and are often used by doctors to diagnose the patient.
Use of computer software is used in Police investigations for facial recognition. This program can identify the face of the suspect by having a record in the police system called the portrait mode with the description the witness gives to the forensic artist.

1. Speech Recognition

Some systems imparted with AI are designed to make them capable of hearing the voice and comprehending the language in order to understand the meaning of the words. This comprehension is not only in terms of the words but also in terms of sentences, their meanings, and the tone while human talks in various languages to the system. The software is built to recognize different accents, dialects, slang words, background noise, changes in voice modulation, changes in the voice due to pain, cold, etc.

2. Handwriting Recognition

This kind of software is programmed so as to read the text. This text can be written using a pen or pencil on paper. The text can also be on a screen written by a mouse or using a stylus. It can read the text and recognize the shapes of the letters and numbers and then convert it into editable text that can be manipulated, changed, and stored, thus, increasing the speed of the process.

3. Intelligent Robots

Robots are machines that are programmed as slaves built to perform the tasks commanded by a master. They are built with various sensors. These sensors read the physical data as input from the real world. This physical data is in the form of light, heat and temperature, movement and pressure, sound, obstruction, spatial coordinates and bump. They are installed with efficient processors, multiple sensors, and huge storage memory. All this is installed to exhibit intelligence. Besides, they are capable of adapting to the changing environment and learning from their mistakes.

Advantages and Disadvantages of AI

Below are the advantages and disadvantages of AI:

Advantages:

The error rate, when compared to the human counterpart, is much lower.
The precision, accuracy, and speed with which AI systems work is incredible.
Can work with equal efficiency in hostile environments.
Complete dangerous tasks which pose challenges to man, it becomes possible to perform tasks like exploring space without any physical damage to humans.
Mining and digging fuels become easy when such machines are used.
Repetitive, monotonous, and tedious tasks can be taken care of without losing on efficiency.
Prediction and Decision Making.
Detecting fraud has become easier, especially in card-based systems.
Organize and manage records.
Robotic pets can be built to interact with people and help reduce depression and inactivity.
Making rational decisions as the machines think logically without emotions.

Disadvantages:

A building, rebuilding, and repairing requires skilled professionals and costs a lot of money and time.
Storage is expensive.
Access and retrieval of data from memory may not be as efficient as the human system.
Machines can be programmed to learn and get better but not as good as humans.
The scope of their operations is restricted to the program written.
They could never receive the creativity that humans have.
Unemployment is the biggest threat because of the development in intelligent machines.
Lazy as humans are, they can become too dependent on machines and underutilize their mental capabilities.
Machines, in the wrong hands, can easily lead to destruction.

Conclusion

This was a short article on the much-hyped word “Artificial Intelligence”. Along with advantages, AI also comes with certain challenges and disadvantages. It is up to the business to evaluate whether investing in such technologies is necessary and profitable.

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