Artificial intelligence

Artificial intelligence

      Artificial intelligence is a branch of science, which exhibits the task performed by humans. Instead of human, machine perform those tasks for humans.
This emerging technology carries out the functions of image processing, translation, voice detection and many more. 
With the help of AI there has been a major change in the field of science and technology. In this paper Introduction to Artificial intelligence, background, implementation in various fields with regards to day to day life, pros and cons of using AI and most importantly the effects of AI in future is elaborated. 
Keywords: Virtual intelligence , neurons , cognitive science, machine learning , humanoid , robotics , artificial neural network,


 Introduction

     Introduced in the year 1956, in a small workshop where the researchers from Carnegie Mellon University (CMU), Massachusetts Institute of University (MIT) and employee of IBM(International Business Machine) together found this potion of incredible as well as unpredictable future, which was Artificial Intelligence(1). 
This truly is one of the major breakthrough in the field of Science and Technology. Making advancement not only in the industry of Computer Science but also in the field of every living room.
AI is the intelligence exhibited by the machine with a close association to that of the human intelligence. It works just as human mind, carrying out all the functions such as problem solving, learning, etc.
One of the major benefits of AI is that as the name suggests, Artificial Intelligence is about it’s curiosity i.e., it is developed to be as curious as humans, to learn and understand new things, it is also capable of completing the tasks given efficiently.

     AI is classified into three categories, i.e., analytical, which has only characteristics consistent with cognitive intelligence; generating intellectual activity (such as thinking, reasoning or remembering), learning based on past experience, to predict and be prepared for the future decisions. Then comes the human-inspired AI, one of the major quality that makes humans put on top of the food chain is the capacity to express emotions in a way no other species can. Learning as well as performing this art of emotions makes AI one of the main reasons to be trending in today’s era. AI has the ability to understand human emotions in addition to cognitive elements, helping them in their decision-making skills. Human inspired  (Artificial intelligence) shows all kinds of characteristics. It is self-conscious and self-aware of its activities. Then comes the humanized AI which has the ability to interact with humans, which makes the grasp of AI strong. All these categories of AI help to form a connection between a machine and human (1).

      As mentioned above, just like the categories say, there were many inventions made on the basis of humanized artificial intelligence. One such example is Sophia, a social humanoid robot which resembles a human, developed by a Hong Kong based company Hanson Robotics. She is able to display more than 50 facial expressions which shows how advanced the field of Artificial Intelligence is.
Background
Though the discovery of AI was  in late 1956, implementation of this technology was not so easy. 
For years there were many failures to connect people and to use AI in every sector, either by lose of funding or lack of support AI was lagging behind.
Later followed by new approaches was it brought into the spotlight. Because of founding fathers of AI namely Alan Turing, Marvin Minsky, Allen Newell, Herbert A. Simon was it possible to make drastic changes.
Alan Turing wrote, “I have no very convincing arguments of a positive nature to support my views”. Because of his thinking that, “Can machines think?” was the base for the new field of AI to generate.
Turing well understood the need for Empirical evidences. Proposing what has become known as the Turing test to determine if machine was capable of thinking. The test was an adaption of a Victorian-style competition called the imitation game.

Which defines the machine to possess the following capabilities 
1) Natural language processing to enable it to communicate successfully in English;
2) Knowledge representation to store what it knows or hears.
3) Automated reasoning to use the stored information to answer questions and to draw new conclusions.
4) Machine learning to adopt to new circumstances and to detect and extrapolate patterns.
 The idea of this game is that the test deliberately avoided direct physical interaction between the interrogator and  the computer, because physical simulation of a person is unnecessary for intelligence. However , the so called total Turing test includes video signal so that the interrogator can test the subjects perceptual abilities as well as the opportunity for the interrogator to pass physical objects through the “hatch” to pass the total Turing test the computer will need. 
5) Computer vision to perceive objects and, 
6) Robotics to manipulate objects and move. 
These six disciplines compose most of AI.
Turing’s Test was a strong inspiration and supported the concept of AI(1) .

Why Why artificial intelligence?


     AI has become one of the most important tool. It is used in lot of sectors. It can understand your handwriting, your voice. It cannot understand what you are thinking exactly, but can come close to what you may, it can predict. While humans are smart and good at performing a number of tasks, machines can do it much better, if programmed in a right manner. What makes AI perform better is the ability to learn and make its own decisions. 


How does AI work?

     Computers need to be said what they have to do. They do not make their own decisions. So how do you make them do the thinking?. This is the issue of machine learning. Here the computer’s ability is to do two things, first, make its own decisions. Second, make predictions. In this way, a good AI makes minimal errors.

How to achieve machine learning?


Algorithms!!
     It works differently for different circumstances. To get the best idea of how it works, one is to focus on the popular NYD method. Most AI are biologically inspired computing. It works on simulated thinking, just like simulated brain. It’s a kind of simulated machine, which can make different decisions for given different circumstances. This is the basis for neural network. 
In a neural network, simulation takes place where the system takes in the information, which is simulated by the bunch of neurons, by which the other neurons are simulated. The whole process repeats until the final result is acquired.
An artificial consists of a pool of simple processing units which communicate by sending signals to each other over a large number of weighted connections. A set of major aspects of a parallel distributed model include:
A set of processing units (cell).
A set of activation for every unit, which is  equivalent to the output of the unit.
Connection between the units. Generally each connection is defined by a weight.
A propagation rule, which determines the effective input of a unit from its external inputs.
A method for information gathering (the learning rule).
An environment within which the system must operate, providing input signals and if necessary error signals.
There are two basic reasons why we are interested in building artificial neural networks (ANNs).
 1) Technical viewpoint: some problems such as character recognition or the prediction of future states of a system require massively parallel and adaptive processing.
2) Biological viewpoint: ANNs can be used to replicate and simulate components of the human (or animal ) brain, thereby giving us the insight into the natural information.
The “building blocks “ of neural network are the neurons .
In technical system, we also refer to them as units or nodes.
Basically, each neuron:  receives input from many other neuron, changes its internal state (activation ) based on the current input and sends one output signal to many other neurons, possibly including its input neurons (recurrent network).
Information is transmitted as a series of electric impulses, so-called spikes.
The frequency and phase of these spikes encodes the information. In biological system, one neuron can be connected to as many as 10,000 other neurons usually, a neuron receives its information from other neurons in a confined area, its so-called receptive field.
An ANN is either a hardware implementation or a computer program which strives to simulate the information processing capabilities of a great number of interconnected artificial neurons. The artificial counterparts.
ANN is a technique for solving problems by constructing software that works like the brain. Brain is a massively parallel information system , our brains are a huge network of processing elements. A typical brain contains a network of 10 billion neurons. And Artificial intelligence also has to work the same way as the brain does and with the help of neural network AI can perform tasks that humans can and identify the images. In terms of biological neurons dendrites are considered as input cell body the processor synaptic a link and axon the output. In the processing element a neuron is connected to other neurons through about 10,000 synapses a neuron receives input from the other neuron. Inputs are combined once input exceeds a critical level, the neurons discharges a spike- an electrical pulse that travels from the body, down the axon, to the next neuron(s) the axon ending almost touch the dendrites or cell body of the next neuron. Transmission of an electrical signal from one neuron to the next is effected by neurotransmitters there’s a link of these neurotransmitters called synapse .the strength of the signal that reaches the next neuron on the factors such as the amount of neurotransmitter available(3).
 And in the similar fashion the ANN works i.e, An artificial neuron is a imitation of a human neuron, a single neuron :x1,x2,x3,x4,x5…xn is inputed through   summation unit    and by the help of transfer function the output is fed to the other neurons. The input x1,x1….xn is processed and if the sum of the input is equal to output than the information is processed correctly, but in some cases not all the inputs are equal to the output, there the weights are added to the input  during processing and the sum of input and the extra added weights are made equal to the output, yet in some cases the signal inn not passed down to the next neuron verbatim, ie the inputs x1,x2 do not reach the input x3 making it difficult to calculate the  sum of input given then is such situation transfer function or activation function is conducted, for the input to be made equal to the output. The output  is a function of the input, that is affected by the weights and the transfer function. Later on three layers : input, hidden and output are displayed. 

     An ANN can; compute any computable function, by the appropriate selection of the network topology and weights values. Specially by trial and error method. 
 In artificial intelligence wherein the neural network works to find a perfect solution and identify the entity presented a continues process of trial(processing an input to produce an output, evaluate(evaluating this output by comparing the actual output with the expected output and adjustment  of weights is done. 

Implementation



     Artificial intelligence in today’s generation is used almost everywhere. There isn’t a place where AI is not of importance, from driving your car to securing your homes AI is used. Many Online shopping sites have made their mark by switching to Artificial intelligence. Amazon Alexa, known simply as Alexa is a virtual assistant developed  by Amazon ,first used in Amazon Echo smart speaker developed by Amazon Lab126. It is capable of voice interaction ,music playback, making to do list, setting alarms ,streaming podcast and other real time information .
Since Amazon has adopted this new technology their revenue has increased drastically. Also, in the field of E-marketing AI plays a major role. Due to AI, a lot of internet based companies have improved and gained extensive popularity. They are able to easily connect to their consumers and identify their requirements and in this way it’s easier for them to provide the consumers what they are actually looking for and not showcasing any random product in front of them. 
In the same way Apples Siri developed by Apple also is again a virtual assistant. A virtual assistant is a AI which performs most of the tedious task which humans are unable to do, an AI can check the weather report and inform you , sense your voice , finger print ,detect face and understand your emotions.\

     Common sector where AI is used: medical diagnosis, banks, educational sectors, aeronautical engineering, robotics, finance, transportation, agriculture(predictive analytics, modelling), military; majorly in the field of computer science. It is also used in many of the universities for research purpose, algorithm trading, now a days it’s also very helpful in the field of media and communication, management, etc.
In case of hospitals, artificial neural networks are used for clinical decision support system for medical diagnosis such as in the concept processing technology in EHR(Electronic Health Record).

Example: 

Robotically assessed brain surgery and its performance.
From the two optical outputs, the computer generates a 3D image of the surgical site for the surgeon to view. The system control pedals provide precise camera control so that surgeon can instantly zoom  in and out to change the surgical view(2).
Artificial Intelligence works differently in different sectors. In case of medical diagnosis the AI works in a way it’s helpful for the surgeon to save the patient .and in case of  transportation it only concentrates on giving the passenger the right direction and doesn’t give unwanted information. All of this explains that  AI works the way it is programmed to. In the field of AI itself there are several subdivisions which help understand the different kinds of fields surrounded around human beings ,that makes a huge change in the way of living. 

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