11. Artificial Intelligence
In today's world, technology is growing very fast, and we are getting in touch with different new technologies day by day.
Here, one of the booming technologies of computer science is Artificial Intelligence which is ready to create a new revolution in the world by making intelligent machines.The Artificial Intelligence is now all around us. It is currently working with a variety of subfields, ranging from general to specific, such as self-driving cars, playing chess, proving theorems, playing music, Painting, etc.
AI is one of the fascinating and universal fields of Computer science which has a great scope in future. AI holds a tendency to cause a machine to work as a human.
What is Artificial Intelligence?
Artificial Intelligence is composed of two words Artificial and Intelligence, where Artificial defines "man-made," and intelligence defines "thinking power", hence AI means "a man-made thinking power."
So, we can define AI as:
"It is a branch of computer science by which we can create intelligent machines which can behave like a human, think like humans, and able to make decisions."
Artificial Intelligence exists when a machine can have human based skills such as learning, reasoning, and solving problems
With Artificial Intelligence you do not need to preprogram a machine to do some work, despite that you can create a machine with programmed algorithms which can work with own intelligence, and that is the awesomeness of AI.
It is believed that AI is not a new technology, and some people says that as per Greek myth, there were Mechanical men in early days which can work and behave like humans.
Why Artificial Intelligence?
Before Learning about Artificial Intelligence, we should know that what is the importance of AI and why should we learn it. Following are some main reasons to learn about AI:
With the help of AI, you can create such software or devices which can solve real-world problems very easily and with accuracy such as health issues, marketing, traffic issues, etc.
With the help of AI, you can create your personal virtual Assistant, such as Cortana, Google Assistant, Siri, etc.
With the help of AI, you can build such Robots which can work in an environment where survival of humans can be at risk.
AI opens a path for other new technologies, new devices, and new Opportunities.
Goals of Artificial Intelligence
Following are the main goals of Artificial Intelligence:
Replicate human intelligence
Solve Knowledge-intensive tasks
An intelligent connection of perception and action
Building a machine which can perform tasks that requires human intelligence such as:
Creating some system which can exhibit intelligent behavior, learn new things by itself, demonstrate, explain, and can advise to its user.
What Comprises to Artificial Intelligence?
Artificial Intelligence is not just a part of computer science even it's so vast and requires lots of other factors which can contribute to it. To create the AI first we should know that how intelligence is composed, so the Intelligence is an intangible part of our brain which is a combination of Reasoning, learning, problem-solving perception, language understanding, etc.
To achieve the above factors for a machine or software Artificial Intelligence requires the following discipline:
Mathematics
Biology
Psychology
Sociology
Computer Science
Neurons Study
Statistics
Advantages of Artificial Intelligence
Following are some main advantages of Artificial Intelligence:
High Accuracy with less errors: AI machines or systems are prone to less errors and high accuracy as it takes decisions as per pre-experience or information.
High-Speed: AI systems can be of very high-speed and fast-decision making, because of that AI systems can beat a chess champion in the Chess game.
High reliability: AI machines are highly reliable and can perform the same action multiple times with high accuracy.
Useful for risky areas: AI machines can be helpful in situations such as defusing a bomb, exploring the ocean floor, where to employ a human can be risky.
Digital Assistant: AI can be very useful to provide digital assistant to the users such as AI technology is currently used by various E-commerce websites to show the products as per customer requirement.
Useful as a public utility: AI can be very useful for public utilities such as a self-driving car which can make our journey safer and hassle-free, facial recognition for security purpose, Natural language processing to communicate with the human in human-language, etc.
Disadvantages of Artificial Intelligence
Every technology has some disadvantages, and thesame goes for Artificial intelligence. Being so advantageous technology still, it has some disadvantages which we need to keep in our mind while creating an AI system. Following are the disadvantages of AI:
High Cost: The hardware and software requirement of AI is very costly as it requires lots of maintenance to meet current world requirements.
Can't think out of the box: Even we are making smarter machines with AI, but still they cannot work out of the box, as the robot will only do that work for which they are trained, or programmed.
No feelings and emotions: AI machines can be an outstanding performer, but still it does not have the feeling so it cannot make any kind of emotional attachment with human, and may sometime be harmful for users if the proper care is not taken.
Increase dependency on machines: With the increment of technology, people are getting more dependent on devices and hence they are losing their mental capabilities.
No Original Creativity: As humans are so creative and can imagine some new ideas but still AI machines cannot beat this power of human intelligence and cannot be creative and imaginative.
What is Artificial Intelligence?
According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”.
Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.
AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.
Philosophy of AI
While exploiting the power of the computer systems, the curiosity of human, lead him to wonder, “Can a machine think and behave like humans do?”
Thus, the development of AI started with the intention of creating similar intelligence in machines that we find and regard high in humans.
Goals of AI
To Create Expert Systems − The systems which exhibit intelligent behavior, learn, demonstrate, explain, and advice its users.
To Implement Human Intelligence in Machines − Creating systems that understand, think, learn, and behave like humans.
Applications of AI
AI has been dominant in various fields such as −
Gaming − AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge.
Natural Language Processing − It is possible to interact with the computer that understands natural language spoken by humans.
Expert Systems − There are some applications which integrate machine, software, and special information to impart reasoning and advising. They provide explanation and advice to the users.
Vision Systems − These systems understand, interpret, and comprehend visual input on the computer. For example,
A spying aeroplane takes photographs, which are used to figure out spatial information or map of the areas.
Doctors use clinical expert system to diagnose the patient.
Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist.
Speech Recognition − Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human’s noise due to cold, etc.
Handwriting Recognition − The handwriting recognition software reads the text written on paper by a pen or on screen by a stylus. It can recognize the shapes of the letters and convert it into editable text.
Intelligent Robots − Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors and huge memory, to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to the new environment.
AI knowledge cycle:
An Artificial intelligence system has the following components for displaying intelligent behavior:
The above diagram is showing how an AI system can interact with the real world and what components help it to show intelligence. AI system has Perception component by which it retrieves information from its environment. It can be visual, audio or another form of sensory input. The learning component is responsible for learning from data captured by Perception comportment. In the complete cycle, the main components are knowledge representation and Reasoning. These two components are involved in showing the intelligence in machine-like humans. These two components are independent with each other but also coupled together. The planning and execution depend on analysis of Knowledge representation and reasoning.
11.1 Search
11.2 Natural Language Processing
Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English.
Processing of Natural Language is required when you want an intelligent system like robot to perform as per your instructions, when you want to hear decision from a dialogue based clinical expert system, etc.
The field of NLP involves making computers to perform useful tasks with the natural languages humans use. The input and output of an NLP system can be −
Components of NLP
There are two components of NLP as given −
Natural Language Understanding (NLU)
Understanding involves the following tasks −
Natural Language Generation (NLG)
It is the process of producing meaningful phrases and sentences in the form of natural language from some internal representation.
It involves −
Text planning − It includes retrieving the relevant content from knowledge base.
Sentence planning − It includes choosing required words, forming meaningful phrases, setting tone of the sentence.
Text Realization − It is mapping sentence plan into sentence structure.
The NLU is harder than NLG.
Difficulties in NLU
NL has an extremely rich form and structure.
It is very ambiguous. There can be different levels of ambiguity −
Lexical ambiguity − It is at very primitive level such as word-level.
For example, treating the word “board” as noun or verb?
Syntax Level ambiguity − A sentence can be parsed in different ways.
For example, “He lifted the beetle with red cap.” − Did he use cap to lift the beetle or he lifted a beetle that had red cap?
Referential ambiguity − Referring to something using pronouns. For example, Rima went to Gauri. She said, “I am tired.” − Exactly who is tired?
One input can mean different meanings.
Many inputs can mean the same thing.
Steps in NLP
There are general five steps −
Lexical Analysis − It involves identifying and analyzing the structure of words. Lexicon of a language means the collection of words and phrases in a language. Lexical analysis is dividing the whole chunk of txt into paragraphs, sentences, and words.
Syntactic Analysis (Parsing) − It involves analysis of words in the sentence for grammar and arranging words in a manner that shows the relationship among the words. The sentence such as “The school goes to boy” is rejected by English syntactic analyzer.
Semantic Analysis − It draws the exact meaning or the dictionary meaning from the text. The text is checked for meaningfulness. It is done by mapping syntactic structures and objects in the task domain. The semantic analyzer disregards sentence such as “hot ice-cream”.
Discourse Integration − The meaning of any sentence depends upon the meaning of the sentence just before it. In addition, it also brings about the meaning of immediately succeeding sentence.
Pragmatic Analysis − During this, what was said is re-interpreted on what it actually meant. It involves deriving those aspects of language which require real world knowledge.
Application of NLP
1.Speech Recognition
2.Sentimental Analysis
3.Machine Translation
4.Chat Boxes,etc
11.3 Game Playing
11.4 Learning
Machine learning evolved from left to right as shown in the above diagram.
Initially, researchers started out with Supervised Learning. This is the case of housing price prediction discussed earlier.
This was followed by unsupervised learning, where the machine is made to learn on its own without any supervision.
Scientists discovered further that it may be a good idea to reward the machine when it does the job the expected way and there came the Reinforcement Learning.
Very soon, the data that is available these days has become so humongous that the conventional techniques developed so far failed to analyze the big data and provide us the predictions.
Thus, came the deep learning where the human brain is simulated in the Artificial Neural Networks (ANN) created in our binary computers.
The machine now learns on its own using the high computing power and huge memory resources that are available today.
It is now observed that Deep Learning has solved many of the previously unsolvable problems.
The technique is now further advanced by giving incentives to Deep Learning networks as awards and there finally comes Deep Reinforcement Learning.
11.5 Automated reasoning
11.6 Planning
11.7 Vision and Robotics
