Introduction to Artificial Intelligence

Introduction to Artificial Intelligence

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Artificial Intelligence (AI) as the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

The Oxford Dictionary defines Artificial Intelligence.

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Hello there, Here is a brief introduction for Artificial Intelligence. Do you recognize above picture? Yeah, That's Wall-E. An Award winning animated films that everyone fallen love with. Wall-E, a robot who has achieved sentience, is the only robot of his kind shown to be still functioning on earth in the 29th century. He thinks, make decisions, and curious. You'll think why i would mention about this animated movie. So who would think a cute little robot can actually have the ability to think and make decisions, most importantly have emotions like humans?

What is Artificial Intelligence?

Artificial Intelligence is an approach to make a computer, machines or a products capable of performing tasks that typically require human intelligent. Simply a approach to make machines to think like how smart human think. The aim of AI is to improve computer functions which are related to human knowledge, for example, reasoning, learning, problem solving.

AI is frequently applied to the projects of developing systems with the intellectual processes characteristic of humans, such as ability to learn, ability to think, ability to reason, discover meaning learning from the past or learning from the experience. With the evolution of the digital computers, they were able to programmed to carry out more and more complex tasks. Such as playing Sudoku, playing chess, usage for proofing the mathematical theorems. Then the scientists are came with the idea, what if the computers have the ability to think like humans. That's the beginning of the AI concept.

Since then it has been evolved more and more. Now we have some programs that can attain the performance level of human experts and professionals in performing certain tasks. For example Handwriting recognition, medical diagnosis, self driving car, voice recognition, search engines, etc. but yet no programs that can match the human flexibility over wider domain. But as i mentioned before we are able to achieve certain level of artificial intelligence. So artificial intelligence is not just a science-fiction dream. It will become reality in the near future.

What is Intelligence?

Intelligence is the ability to learn from experience, to solve problems, and to adapt to new situations. The intelligence is intangible and it is composed of

• Reasoning

• Learning

• Problem Solving

• Perception

• Linguistic Intelligence

Reasoning

Reasoning it to draw inferences appropriate to the situation. It is the set of processes that enables us to provide basis for judgement, making decisions, and prediction. The inferences (Reasoning) are classified to two types as "Inductive" or "Deductive". We can simply explain what are those by using a simple example.

Inductive Reasoning, "Jimmy must be either driver or carpenter. Jimmy is not a driver. Therefore jimmy is a carpenter."

Deductive Reasoning, "A person of age equal or above 18 is an Adult. Angela is 20 years old. Therefore, Angela is an Adult."

the difference between these forms of reasoning is that the deductive reasoning, the truth of the premises guarantees the truth of the conclusion. but in inductive reasoning, the truth of the premise lends support to the conclusion without giving absolute assurance.

There has been considerable success in programming computers to draw inferences. Specially deductive reasoning. However, true reasoning is one of the hardest problems you will found when it comes to AI. Because true reasoning involves more than just drawing inferences. It involves drawing inferences relevant to the solution of the particular task or situation. So there you have to think each and every possible solutions and tasks and then draw the inferences. You will understand this when it comes to "Expert Systems". That makes this as one of the hardest problems confronting AI.

Learning

Learning is the activity of gaining knowledge or skill by studying. practicing, being taught, or experiencing something. Learning enhances the awareness of the subjects of the study. There are number of different forms of learning as applied to AI.

Auditory Learning, it is learning by listening and hearing. (for example, Students listening to recorded audio lectures.)

Episodic Learning, To learn by remembering sequences of events that one has witnessed or experienced. This can be linear and orderly. (for example, Mass solving robot)

Motor Learning, It is learning by precise movement of muscles. (for example, Writing, picking objects and placing them)

Observation Learning, To learn by watching and imitating others. (for example, child try to learn by mimicking parents)

Perceptual Learning, It is learning to recognize stimuli that one has seen before. (for example, Identifying and classifying objects)

Relational Learning, It involves learning to differentiate among various stimuli on the basis of relational properties. rather than absolute properties. (for example, Previously put one tablespoon of salt, but becomes salty. then the next time says all a little less than one tablespoon of salt)

Spatial Learning, It is learning through visual stimuli such as images, colors, maps. (for example, self driving car drives by a person before it has driving on its own)

Stimulus-Response Learning, It is learning to perform a particular behavior when a certain stimulus is present (for example, Crossing road when cross way signal turns green)

Problem Solving

Problem solving is the process in which one perceives and tries to arrive at a desired solution from a present situation by taking some path. It can be characterized as a systematic search through a range of possible actions in order to reach some predefined goal or solution. This includes "decision making", which is selecting best suitable alternative out of multiple alternatives to reach the desired goal. Problem solving method can further categorized as "Special Purpose" and "General Purpose".

Special purpose, Often exploits very specific features of the situation in which the problem is embedded.

General purpose, means incremental (step by step) reduction of the difference between the current state and the final goal.

Perception

Perception is the process of acquiring, interpreting , selecting, and organizing sensory information in a meaningful manner. In humans, perception is aided by sensory organs. In AL perception mechanism puts the data acquired by the sensors together in a meaningful manner.

Linguistic Intelligence

This is one's ability to use, comprehend, speak, and write the verbal and written language. This is important in interpersonal communication. For further clarification, Computer does not know the human language. But it is relatively easy to write computer programs in several restricted context, to respond fluently in a human language to question and statements. Although none of these programs actually understands language. According to the one's theory, whether or not one understands depends not only on one's behavior but also on one's history, in order to be said to understand, one must have learned the language and have been trained to take one's place in the linguistic community by means of interaction with other language users.

Difference between Human and Machine Intelligence

• Humans perceive by patterns whereas, Machines perceive by set of rules and data.

• Human store and recall information by patterns, Machines do it by searching algorithms.

• Humans can figure out the complete object even if some part of it is missing or distorted. Whereas, Machines cannot do it correctly.