What is AI and Its Main Applications

What is AI?

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

Main Applications of AI

Expert System

Expert systems (ES) are one of the prominent research domains of AI. It is introduced by the researchers at Stanford University, Computer Science Department. These systems are the computer applications developed to solve complex problems in a particular domain, just like human experts. Expert systems are ideal when it is necessary for an individual to select the best alternative from a long list of choices. Based on the criteria supplied to it, the expert system can choose the best option. For example, there are expert systems that will help you to select one of the many places to invest your money based on your own financial conditions, goals, and personality traits. An ES includes following main components:
1: Knowledge Base
It contains the knowledge related to specific domain. What is Knowledge? The data is collection of facts. The information is organized as data and facts about the task domain. Data, information, and past experience combined together are termed as knowledge.
2: Inference Engine It acquires and manipulates the knowledge to reach to a solution from multiple solutions.
3: User Interface: It provides interaction between user and ES.


Natural Language Processing NLP

Natural Language Processing, usually shortened as NLP, is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language (voice or text). The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable. Generally, the output of NLP can be Speech or Written Text. It has three basic parts: 

1: Parser:The parser takes the natural language input sentence and breaks it down into the various parts of grammar (nouns, verbs, adjectives, prepositions, etc.). This is the first step in determining the function of each word in the sentence and the way the words related to one another. This analysis usually results in construction of parse tree. A dictionary associatedwith the parser helps determine word meaning

2: Knowledge Base:It analyses the data came from parser with associated dictionay meanings. It then tries to take some action on basis of input received from parser.

2: Output Translator:It takes input from Knowledge Base system and performs some action or produces some ouput. Ouput may be speech in some other Natural Language or same language that is entered or it may produce some results in written form.


Speech Recognition and Generation

It allows users to interact with system via voice. One of the most common application of speech recognition and Generation is Microsoft’s Cortana used in win 8 and win 10. Other applications of voice recognition are Google’s speech recognition system and Apple’s Sirri. In early 2014, Amazon released the Amazon Dash, a portable device that one can use to compile a grocery list by voice recognition. The output of the voice reconition can be used to drive a natural language processing system and the NLP will take actions according to voice commands.



Neural Networks

Artificial neural networks (ANN) are computing systems that are inspired by, but not identical to, biological neural networks that constitute animal brains. Such systems "learn" to perform tasks by considering examples, generally without being programmed with task-specific rules. For example, in image recognition, they might learn to identify images that contain cats by analyzing example images that have been manually labeled as "cat" or "no cat" and using the results to identify cats in other images. They do this without any prior knowledge of cats, for example, that they have fur, tails, whiskers and cat-like faces. Instead, they automatically generate identifying characteristics from the examples that they process.

An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses (a structure in brain which allows neurons to send signal to other neurons) in a biological brain, can transmit a signal to other neurons. An artificial neuron that receives a signal then processes it and can signal neurons connected to it. ANNs have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games, medical diagnosis and even in activities that have traditionally been considered as reserved to humans, like painting.

Computer Vision

Computer vision is a scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos or Visuals. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to perform a decision. Domains of computer vision are scene reconstruction, video tracking, object recognition, motion sensing and image restoration.

Computer vision extracts information from images through a camera or set of cameras. This information is then converted into digital format with the help of ADC (Analog to Digital Convertor). Once the data is converted into digital format then AI in computer analysis this data and performs the required action.

Virtual Reality

Virtual Reality (VR) is the use of computer technology to create a simulated environment. Unlike traditional user interfaces, VR places the user inside an experience. Instead of viewing a screen in front of them, users are immersed and able to interact with 3D worlds. By simulating as many senses as possible, such as vision, hearing, touch, even smell, the computer is transformed into a gatekeeper to this artificial world. The only limits to near-real VR experiences are the availability of content and cheap computing power. As of the end of 2018, the three-best selling Virtual Reality headsets were Sony’s PlayStation VR (PSVR), Facebook’s Oculus Rift and the HTC Vive. This was not a surprise, seeing as the same three HMDs (Head Mounted Displays) had also been best sellers in 2017. 2019 sees the VR landscape broadening with Google, HP, Lenovo, and others looking to grab a piece of the still-burgeoning market. For Further Details visit these sites:
Oculus From facebook: https://www.youtube.com/embed/-bQUBzPZHHQ
PlayStation VR https://www.youtube.com/embed/-GXvYexMoZY
HTC Vive https://www.youtube.com/embed/i1r76omNeI8

Robotics

Robotics is a domain in artificial intelligence that deals with the study of creating intelligent and efficient robots.It is an interdisciplinary branch of engineering and science that includes mechanical engineering, electronic engineering, information engineering, computer science, and others.This field of science is concerned with the development of machines that can


substitute humans and replication human actions. Robots can be used in many situations and for lots of purposes like today they are used dangerous environments like deactivation of bombs, in manufactring processes or in those situations where humans cannot survive like space, water, in high temprature and cleaning up hazardous materials and radiations.

Current Potential Uses of Robots

• Construction Robots
• Agricultural Robots
• Combat Robots
• Medical Robots
• Humaniod Robots
• Military Robotics