Artificial Intelligence: Description, Applications, and Future Scope

Artificial intelligence is a field of computer science concerned with the acquisition of intelligence by computers to make them perform like human beings. This article explores the description of AI, its applications in various industries, related work and models, and the pros and cons of AI. It also discusses the future scope of AI in cybersecurity, face recognition, and drug discovery.

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Abstract
Artificial intelligence is a branch and a field in computer science which is concerned with the
acquisition of intelligence by computers to make them perform like human beings. This field includes
robotics, neural networks, and natural language processing. To date, no computer systems have been
able to simulate and exhibit full intelligence like human beings.
Some of the greatest advancement in the field include the development of chess-playing game which is
now capable of performing better than human beings and even beating them in the matches.
The hottest topics in the field of artificial intelligence are the usage and advancements in neural
networks. Neural networks are very successful is such areas like voice recognition and natural language
processing. Programming forms the integral of the field. Some of the programming languages which
are used in this field include LISP and Prolog
The main efforts that are being achieved by the use of artificial intelligence are the reduction and the
elimination of human efforts in the performance of tasks. Most of the tasks are now being controlled by
machines, which even perform better than humans.
Table of Contents

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Abstract......................................................................................................................................................2
Introduction................................................................................................................................................4
Description of Artificial Intelligence.........................................................................................................5
AI Applications.................................................................................................................................8
Related work and AI models.............................................................................................................9
Future scope of AI....................................................................................................................................14
Conclusion...............................................................................................................................................16
References................................................................................................................................................17

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Introduction
The reason for the choice of this topic is the technological advancements in the field of Artificial
intelligence [1]. Therefore; I will introduce aspects related to AI including the advantages and the
disadvantages which are associated with the use of this technology. The algorithms which are used in
production system for AI will also be introduced .
The central goals and the attributes in this field include reasoning, learning and the ability to move
objects from one point to another, including manipulation of objects. Today, this field forms the most
essential part of the industry of technology whose main focus is finding solutions to the most difficult
problems in computing.
Mathematical optimizations and logic methods are some of the tools which are used to enhance the
usage and the improvement of AI. Logic forms an integral part in understanding the operations and the
reasoning behind the implementation of the technology.

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Description of Artificial Intelligence
Artificial Intelligence can be described as the field of study which is mainly focused on the capability
that machine learning techniques can be able to respond under certain circumstances just like human
beings [2]. The need and the usage of AI are becoming an increasing factor each day. The rapid changes
in business activities through the use of technology has been brought about by the use of AI. AI was
initially brought about in a marketing field and hence the reason for the high growth rate in the business
sector .
Computer prediction has stated that in the next 10 years, most of the customer's interactions will be
based on machines and not humans. Most of the transactions will not involve the use of humans. This is
an implication that humans will mostly be dependent on the use of computers.
Artificial intelligence studies human behavior, for instance, the working of the human brain, learning
and decision making of humans. These are attempts to capture the outcomes which then form the basis
of engineering intelligent systems and machines .
The mains goals and the philosophy of AI can be described as [3]:
 Development of intelligent and Expert systems. The system developed through the use of AI
should be able to exhibit intelligent behaviors such as a system which is able to learn, explain
and demonstrate the outcomes.
 Implementation of human intelligence in computer systems – the creation and development of
systems which are able to understand human behavior, learn and perform just like human beings
and even better.
AI can be classified depending on the task it is meant to perform. For instance, AI models which is
trained to perform a specific task can be described as a weak AI whereas an artificial intelligent agents
which can be able to perform generic tasks when presented with a new task can be termed as a strong
AI. An AI which is able to find a solution to a problem when presented with an absolutely unfamiliar
task can be defined as a strong AI.

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The operation and the use of AI is expensive since it involves a lot of overhead costs such as, the cost
of hardware and software used in the design and implementation of the intelligent systems.
While the usage and the advancement of the technology in business are progressive, human behavior
must be monitored in the process of training of the data, since a human is only able to select the data
that is needed for training. Most the deep learning algorithms can be used to undermine the operations
and usage of the AI since these algorithms are intelligent and smart enough when given certain data for
training.
The discovery of augmented intelligence is meant to form a basis for humans to be able to understand
the usage of AI to improve the products and services.
Examples of AI technology.
Some of the technologies where the use of AI has been incorporated into include [4] :
 machine-learning – this can be defined the science of making a computer system act and behave
without the use of programming. The prediction of analytics and its automation can be defined
as deep learning which is a subset of machine learning. Some of the algorithms which are used
in machine learning include :
◦ Supervised learning - In this type of learning, the data sets contain a label whose function is
to denote the patterns which can later be used in labeling data sets.
◦ Unsupervised learning – In this type of learning, the data sets do not contain a label, the data
sets are sorted based on similar indexes and others according to their differences.
 Natural language processing - this involves decoding and understanding of the human language
by a computer program. The approaches in language processing are based on machine learning
algorithms. The tasks in this field include, processing of texts and speech recognition. For
instance the analysis of a section of sentiment to detect spam is based on NLP using machine
learning algorithms.

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 Robotics – this is a field of engineering which is mostly focused on the design and the
manufacture of the robotics. These robots are used to perform tasks which the normal humans
can not be able to perform. For example, the assembling of cars in a car production industry is
huge task which can not be performed by humans in a consistent manner, such a task can be
performed by a robotic device.
 Self-driving cars – this involves the combination of both vision and recognition. Deep learning
models are used to train the programs which form piloting for the vehicle and able to avoid
obstacles approaching at a distance. These cars are dependent on intelligent models whose
basis in the field of AI.
AI Applications
These are the fields and the areas in which the development and the use of technology have been
successful [5] .
 Education – an education system is mainly focused on the grading and assessment of the
student needs. The process of assessment and grading can be automated by the use of an AI.
This means that the educators and the tutors can, therefore, be able to focus more on providing
support to the students. The learning paths can be managed and changed by the use of an AI.
 Finance – trading and financial transactions can be managed best using an AI system. Such
applications can be used to collect data and provide real-time calculations which are based the
deliverables. This process is made easier and faster considering the huge number of transactions
which are needed for a certain financial institution [6].

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 Healthcare – companies in the health sector have adopted the use of machine learning programs
and systems which can be used to diagnose patients. The programs are able to mine for the
patient's data and carry out a hypothesis test which is then used to respond and predict the
results. Other activities such as the billing systems and virtual assistants can be provided on the
basis of the use of AI. Technologies such as IBM WATSON, provides the cutting edge which is
used to interpret the natural language from humans and is able to answer and respond to the
questions.
 Manufacturing – This involves incorporation and the use of robots in the industry. These
robotic programs are able to perform tasks that normal human beings can not be able to perform
effectively[7].
 Business - automation can be applied in tasks which keep recurring and are normally
processed and done by human beings [8]. Deep learning algorithms can be incorporated into the
existing platforms to provide assistance and real-time feedback to the customers. For instance
the use of chatbot,, can be able to provide and serve immediate feedback to the customers. Also
the automation of job tasks can be successfully done by the use of business models [9].
Related work and AI models
The operation and the use of AI are mainly focused on the use of algorithms and models which are
based on training. Some of the models and algorithms used include [10] :
 Fuzzy algorithm
 Genetic algorithm
 Decision trees.
 Neural Network
 Deep learning

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Some of the models which are in operation include :
 Support Vector Machine - this can be termed a separating hyperplane which is based on some
training to generate some required output. The algorithm is used to categorize by dividing the
plane in parts with layers on each side [11]. This algorithm has been used in instances such as
pattern classification in an application such as disease diagnosis and treatment. This is based on
a classification model which is based on some training.
Fig
1 :
SVM
in
classification

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Pros and Cons of AI
The use and adoption of AI have aided in solving the mysteries of some of the most complicated
problems. One of the most applied tools in the field of AI called reinforcement learning is based on
finding the success and the failure factors which is used to increase the reliability of applications [12].
Although AI has proven success in business and engineering, the AI is limited in scope to its capability
and functionality .
The huge dependence on AI has it predicted that it could cause the extinction of humans. This is
besides making work easier and saving lives. The reason for the extinction of humans could be due to
efficient and effective operations of the machine learning algorithm in essence to learning.
Advantages of AI
 An AI can not be affected by hostile environment conditions like humans [13]. This means that
the AI can be able to execute some of the most dangerous tasks for instance space exploration.
Humans can not be able to endure the hostile conditions which can even lead to injuries. This
forms the basis of the replacement by the AI programs .
 Fraud detections – AI systems can be able to predict the occurrence of fraud in banking and
even in card-based systems. This can possibly be advanced to check for system failures in
future.
 Prediction – An AI program can be able to predict human behaviors in real-time. The programs
can hence be used in the cases of recommendation systems to the humans. This can provide
real-time assistance to the users since the AI can be able to detect or predict what the user will
type or search at a certain period in time [14].
 Accurate – when fed with accurate information, an AI program will be able to produce the
actual outcomes. The programs are not prone to errors just like humans are. This leads to low
rate of error as compared to humans.

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Disadvantages
 Expensive – The cost involved in the build and the repair of the AI programs is expensive since
it deals with both the hardware and the software. The resources needed for successful
installation and build of a single system is huge [15].
 If the programs and the machines are put in the wrong hands, they can lead to massive
destructions. This causes a lot of fear among humans since the robotic structures can supersede
humans. This can lead to humans being enslaved by robots.
 Massive storage – the storage capacity for the programs and requires expansion every time due
to the huge amounts of data that are used by the programs for the purposes of learning and
training.
Components of an AI
The major components which form the AI include the following :
 User interface
This can be termed as the link between the user and the systems. Since the programs are used for the
purposes of problem-solving, the users are usually linked to the systems using some kind of an
interface. This is where the users are able to interact with the systems directly. A good expert system
should contain a nice look and feel such that the user does not struggle with some of the common
commands while using the systems [16].
After the users query the system, there are a series of responses which are then made back to the user.
The answers are interpreted in such a way that the user can be able to understand them. The interpreted
answers are formed by the system in response to the user queries.

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 Information base
This acts as the storage capacity in which all the rule and the principles that are guiding the usage of the
programs are defined. All the facts and the guidelines that are used by the system to manage the
resources, for instance the prediction are stored and invoked every time the AI programs needs to make
a decision.
This acts as an inference engine which can be accessed at any particular time during processing
and command management for the AI. The rules and the facts which are available in the store are only
known to the particular AI only and can only be interpreted by the AI. The main area of concern for AI
is the ability to optimize and effectively operate using the available storage space. This can assist the
programs to make informed decisions before the prediction of the outcomes and the solutions that are
required to solve a specific task [17].
 Interface Engine
In order for the AI program to execute the defined roles successfully, the information must be retrieved
from the information base. The programs are only able to operate on the basis of using consistent rules
which requires processing. When a user makes a request to the system through the interface. The
request must be processed first to ensure that the AI program understands the request.
Since the program can not be able to operate on what it has not been programmed to. All the rules are
strictly derived and obtained from the storage. The process of analysis and the procedures that are
applied mainly involves the rules and the guidelines form the storage schema.

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Future scope of AI
The simulation and the use of human intelligence in computer systems has been defined as artificial
intelligence. The automation and the use of AI in the field of drug discovery are rapidly growing. This
is mainly because the computing systems have been modeled in such a way that they can be able to
operate just like humans [18] . This has therefore brought about an increase in the efficiency and the
way in which the machines can be able to operate faster in terms of the processing and the prediction .
The scope of AI can be analyzed as follows in each of the given fields:
Cybersecurity
The future of AI will be used in curbing the occurrence of cyber-attacks. Most of the incidences which
are reported in the field of hacking can easily be detected and reported in real-time using the
intelligence of computer systems [19].
Face recognition
In the future, authentication of content can be performed by the use of face recognition techniques.
Government agencies may be able to use this feature to track down cyber-criminal . The feature goes
beyond the physical appearance to analysis of emotions. This can be able to predict and detect if a
human id stressed or not. Identification of citizens by the government agencies can also be done using
this feature which can be automated too.

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Transportation
The emergence of self-driving cars is a clear example of the use and the operation of the artificial
intelligent programs which can be able to perform task without the need for human intervention.
In future, the use of machine learning will be able to model a vehicle which can be able to move
smoothly and able to avoid obstacles. The process can easily be automated to ensure safety and
efficiency in its operation.

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Conclusion
The most significant features and the use of artificial intelligence have been discussed in the research
including the benefits that the technology offers using a precise and clear definition. It can, therefore,
be confirmed that the implementation and build of the technology is not a simple task.
It is not possible to make machine which can be able to think or act like humans. For instance machines
can not be able to show emotions or think like humans under different environmental conditions. Also
the machines can not be able to think or act like humans when exposed to different circumstances.
With the advancement and the growth of the field, it might not be possible to predict the future of AI.
If the machines are able to operate in the same way just like humans, this may definitely lead to the
extinction of the species of humans. This may even change the roles of humans.

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