Artificial Intelligence and It’s Sub-Fields

Artificial intelligence is an area of Computer Science where we develop Intelligent Machines or Computers which are capable to work like humans or mimic their behavior.

Artificial Intelligence can be achieved by Replicating the working of human Brains, which helps machines to take decisions on the basis of certain situations or conditions. Making intelligent machines requires lots of research, as well as practices.

Goals of Artificial Intelligence

Scientific Goal : To determine ideas about knowledge representation, learning,rule systems, search, and so on, explain various sorts of real intelligence.

Engineering Goal : To solve real world problems using AI techniques such as knowledge representation, learning, rule systems, search, and so on.

Implementation Areas of Artificial Intelligence

By the implementation of Artificial Intelligence almost all the sectors of world has been affected or get benefited. But the most benefited sector in which Artificial intelligence is proved like miracle is below :

• Philosophy
• Logic/Mathematics
• Computation
• Psychology/Cognitive Science
• Biological/Neuroscience
• Evolution
• Healthcare

Nowadays all above areas are highly depends on Artificial intelligence in various ways. It makes process more easier a well as faster with good accuracy and capacity.

Sub-Fields of Artificial Intelligence

Artificial Intelligence is having various sub - fields in its domain. All the Sub-Fields can be distinguished as per various techniques. Below are the main fields of Artificial Intelligence in which we are upgrading ourselves day by day :

• Neural Networks
  Neural Networks are inspired by human brains and copies the working process of human brains. It is based on a collection of connected units or nodes called artificial neurons or perceptrons. The Objective of this approach was to solve the problems in the same way that a human brain does. for e.g. brain modelling, time series prediction, classification etc.

• Evolutionary Computations
  Evolutionary algorithms are inspired by biological evolution, and use mechanisms that imitate the evolutionary concepts of reproduction, mutation, recombination and selection. Evolutionary computation techniques can produce highly optimized solutions in a wide range of problem settings. For e.g. genetic algorithms, genetic programming etc.

• Vision
  In Artificial Intelligence Vision (Visioning Applications) means processing any image/video sources to extract meaningful information and take action based on that. In this field of artificial Intelligence we have also developed such kind of robots which are acquiring human activities withing some days or sometimes some hours and train themselves . For e.g. object recognition, image understanding , Playing Robots etc.

• Robotics
  Robots are the artificial agents which behaves like human and build for the purpose of manipulating the objects by perceiving, picking, moving, modifying the physical properties of object, or to have an effect thereby freeing manpower from doing repetitive functions without getting bored, distracted, or exhausted. Robots are not only the part of Computer Science , here Mechanical and Electrical Engineering also plays a big role such as :
  a) AI robots are having mechanical construction and form to accomplish a particular task that can be achieved by Mechanical Engineering .
  b) Robots have electrical components, which power and control the machinery and can be achieved by Electrical Engineering.
  c) And Robots also contains some level of a computer program. That determines what, when, and how a robot does something and here comes the role of Computer Science.

• Expert Systems
  An Expert System is a program that is designed to solve the problems which requires human expertise or experience . By mimicking the thinking of the human experts, the system can perform the analysis, design, or monitoring, make decisions and more.The benefit of this system is Expert knowledge becomes available.
  For e.g. The specialists whom an a professional might like to consult may be not within reach. Also, a specialist may be not aware of modern inventions, new studies and discoveries related to a part of their job. An Expert System can be of great help by offering knowledge of similar cases, especially if used by an international company. Besides, an ES can also serve as a self-check tool.

• Speech Processing
  Speech Processing / Recognition is the ability of a computer and a program to identify words and phrases in the spoken language and convert them to machine readable format.The real life examples of Speech processing are Amazon Alexa and Apple’s Siri Application etc.

• Natural Language Processing
  In the field of natural language processing we mainly focuses on the interactions between human language and computers. NLP is a way for computers to analyze, understand, and derive meaning from human language in a smart and useful way. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation etc.

Machine Learning
The capability of Artificial Intelligence systems to learn by extracting patterns from data is known as Machine Learning. It is an approach or subset of Artificial Intelligence that is based on the idea that machines can be given access to data along with the ability to learn from it.
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. –Tom Mitchell

To understand more about these fields follow the upcoming blog posts.