Topic for this report is: Artificial Intelligence applications and/or research advances1. Please...

Question

Topic for this report is: Artificial Intelligence applications and/or research advances
1. Please check all of the files I attached to see the task description and criteria sheet.

3. It is better to use academic sources, such as journal articles, research papers and academic books. Number of sources for each report should be more than 10.

4. The writing should be academic.

5. In-Text Citations are required, and make a list of references for them, the list of references is not counted into the word count, the citation style is APA.

6. A paragraph of introduction and a paragraph of conclusion for the research report should be written, the article body is between the introduction and conclusion.

7. All of the data, images and tables should be with a title below, and show the sources if it is not original, and include them in the list of references.

8. Plagiarism report (Turnitin) should be provided.

9. Must have Abstract at the beginning.
Thank you very much.

Project Management 1 Student name _______________________________________________________________________________ _______________________________________________________________________________[marking notes] CP5046 ASSESSMENT TASK 4: Research Report © Copyright 2016 This publication is copyright. Apart from any fair dealing for the purpose of private study, research, criticism, or review as permitted under the Copyright Act, no part may be reproduced by any process or placed in computer memory without written permission. ASSESSMENT TASK 4: Research Report Aligned MIT course & CP5046 subject learning outcomes · SLO - Subject Learning Outcomes: SLO-4; · MLO - MIT Course Learning Outcomes: MLO-S4, MLO-S5. Group or individual Individual; (students are allowed to discuss/consult with other students/sources, but the report must be written individually) Weighting / Length 20%; About 3500-4000 words. Due date At the end of last teaching week ASSESSMENT TASK 4: DESCRIPTION The Research Report is the independent research component for this subject. The report must be prepared individually, i.e. one report per student (not per team). The report must apply scientific research methodologies and deliver literature review relevant to the team project. If more than one MIT student are in a team, separate aspects of the team project must be reviewed and analysed, i.e. two or more reports from the same team must not have overlapping content. Topic of the report is very flexible but you must get the topic approved by your subject lecturer. ASSESSMENT TASK 4: CRITERIA SHEET [____/Prerequisite for marking] Report is submitted as a Word (.doc or .docx) document electronically. One submission per student. Marking Rubric: The following table shows the criterion for evaluating your work. Note that there is a big difference between submitting an assessment piece and/or ignoring it (even if the submitted work falls into category 1 of this table). Score 4 3 2 1 Concepts underlying the problem Demonstrates excellent understanding of requisite concepts. Demonstrates Good understanding of requisite concepts. Demonstrates partial understanding of the necessary concepts. Fails to demonstrate a grasp of the concepts. Documentation Description of solution, including any assumptions is fully worked out Description of the solution is understandable but incomplete Insufficient documentation of method and assumptions although a partial solution is presented No, or unintelligible description Solution Problem is fully solved Problem is partially solved Proposed solution is incorrect No solution is presented In general, marking scheme of assignments is in compliance with the above table. The distribution of marks is roughly as follows: Solutions that fall in category 1, will receive at most 15% of the marks assigned to the question. Solutions that fall in category 2, will receive at most 40% of the marks assigned to the question. Solutions that fall in category 3, will receive at most 70% of the marks assigned to the question. Solutions that fall in category 4, will receive at most 100% of the marks assigned to the question. Your solution must be neat and precise, and include your name, comments, and references (if any). Reference course and learning outcomes subject learning outcomes · SLO-1 - Communicate technical information clearly through presentations, demonstrations and documentation; · SLO-2 - Choose and apply the appropriate agile methodologies; · SLO-3 - Evaluate and select appropriate tools and technologies to meet project requirements · SLO-4 - Develop a general knowledge of industry standard project management approaches; · SLO-5 - Critically reflect on progress to tailor self learning goals to advance professional development; · MLO-K1 - Critically analyse to select appropriate tools and technologies to meet project requirements; · MLO-K2 - Evaluate industry standard contexts for project management approaches; · MLO-S4 - Apply lateral and original thinking to conceptualise and evaluate a range of solutions to relevant problems; · MLO-S5 - Communicate technical information clearly through presentations, demonstrations and documentation; · MLO-A1 - Apply appropriate tools and technologies to meet project managements; · MLO-A3 - Critically reflect on progress to tailor self-learning goals to advance professional development. Page 1[Insert Subject Code]

unifolks_636720732416961647_121103_1.docx

Monika · Accepted Answer

Artificial intelligence applications and research advances
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Artificial intelligence applications and research advances
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Table of Contents
1)Abstract
2)Introduction
3)Analysis
3.1)Artificial intelligence
3.2)Current state of AI
3.3)Technologies of artificial intelligence
3.4)Applications of artificial intelligence
3.4.1)Artificial intelligence in Education
3.4.2)Artificial intelligence in Healthcare
3.4.3)Artificial intelligence in Business
3.4.4)Artificial intelligence in Autonomous Vehicle
3.4.5)Artificial intelligence in finance and banking
3.4.6)Artificial intelligence in transportation
3.4.7)Artificial intelligence in aviation
3.4.8)Artificial intelligence in music
3.4.9)Artificial intelligence in games
3.4.10)Artificial intelligence in media and entertainment
4)Future research in AI applications
5)Risks associated to AI Applications
6)Recommendations
7)Conclusion
8)References
Abstract
In this assignment, the report is prepared for the topic of artificial intelligence application and research advances. There is several application of artificial intelligence in different areas or different industry with different technology.  As many business and industry adopted the artificial intelligence and replaced the human being by machine. The major concern is that human being is unethically fired from the job due to his employment cost. And machines are takeover their places.
In this report, firstly we introduced the artificial intelligence and the current state of artificial intelligence. Then we discussed the application of artificial intelligence in different area such as: education, healthcare, business, aviation, media and entertainment, music industry, finance and banking industry, automation vehicle industry, gaming industry and transportation industry. Artificial intelligence reduces the work of human in this application. Now there are coming several startups which are base on AI. The several tools of AI are discussed in report such as siri, tesla, fuzzy logic and neural network etc. the future research of Artificial intelligence application will also discuss in the report.
Artificial intelligence applications and research advances
Introduction
 In all over world, the landscape of business has changed by artificial intelligence dramatically. It is basically a rule based automation that is capable of mimicking the interaction of human. The uniqueness of artificial intelligence is not only due to the human capabilities. The advance algorithm of Ai offered the reliability and better speeds at very low cost in comparison to human counterparts.
In the current environment, artificial intelligence is an umbrella term that performed everything from the automation process of robotics to the robotics actually. There are several tasks performed by AI such as AI identified pattern from data efficiently in comparison to human and enabled business to gin mo from the data. So the massive amount of data analyzed by use of AI to map predict patterns of consumption, healthcare, irrigation and  agriculture, climate change, poverty, waste management and energy usages.
Analysis
Artificial intelligence
Artificial intelligence is defined as a breakthrough technology. But according to John McCarthy who is the father of artificial intelligence; Artificial intelligence is an engineering and science that are making intelligence machine especially for the computer program of intelligence. In other words, it is the process of machine of human intelligence simulation is known as AI. Machine vision, speech recognition and experts system are included by some of the application of AI. There is advancement in AI dramatically. Artificial intelligence transferred all over world politically, economically and socially.
 The main goals of AI are implementation of human intelligence in machines and creation of expert systems, knowledge representation, planning, problem solving, motion and manipulation, perception, natural language processing, general intelligence and social intelligence. Basically AI is a technology and science which are based on the discipline such as biology, science, mathematics and psychology, engineering and computer. Real life examples of AI are: chat bots, self driving car, ASIMO, Boston dynamic, navigation system etc (Admin, 2017).
Current state of AI
In today’s environment, three are several application of AI in the business and consumer spaces from the Siri of apple to Deepmind of Google. For interpreted voice command and respond, Siri used natural language processing and deep learning used by Deepmind of Google accordingly. The efficiency of power center of Google is also improved by reducing energy and applied Deepmind findings .In some industries analytics process and business intelligence are automated by AI and provide end to end holistic solution.
 The work of business and industry are smarter and faster that enabled by artificial intelligence in this business world. Sophisticated and powerful solutions are looking by many organizations for the improvement of operation of streamline as the advancement of technology and society.  But the import fact is that artificial intelligence behaves like umbrella for many different technologies such as computer vision, robotics, deep learning, machine learning, knowledge reasoning, natural language processing, cognitive computing and artificial general intelligence. This is true about AI that it provides extraordinary capabilities and benefits to the industries and business.
If we see the current state of artificial intelligence then we find that many of the application of AI are considered too weak artificial intelligence and many of them are considered to strong AI. 
Weak Artificial intelligence:
The Weak AI is non sentient artificial intelligence which is also known as “Narrow AI” that focus only one task alone. Means the currently available artificial intelligence application are directed to provide the needs of users. The specific situation is respond by machines with weak AI but it can’t able to think for them.
Strong Artificial intelligence:
 Strong Artificial intelligence is also known as general artificial intelligence. In strong AI, the decisions can be formulated by application of artificial intelligence without the need of human input, it can be applied on multiple problems and AI behaves like more than a human being. Strong AI machines are able to think just like human being. It learnt from experiences. Yet presently we have no real life strong AI examples in all over world.
 If we see that some forms of artificial intelligence have been already incorporated by many industries and business in its day to day processes (Ghosh, 2018).
Types of artificial intelligence
There are several ways in which artificial intelligence can be classified. As we discussed above that there are two type of Artificial intelligence that is weak AI and strong AI. According to Arend Hintze, there are four other categories of AI. These are:
Type 1: Reactive machine:
An IBM chess program that is Deep Blue identified the pieces of chess board and make prediction accordingly. It does not have any past experience and even don’t have any memory, these are the major fault of it. For narrow purpose AlphaGO and Deep Blue are designed.
Type 2: Limited memory
Here past experience can be used by these AI systems for informing the decisions of future. For example the design of autonomous vehicles has the decision making function mostly.
Type 3: Theory of Mind
In this case, the decisions are impacted by intentions and beliefs. Actually it is a psychology term. Presently, there is no existence of this type of term.
Type 4: self awareness
In this type of category, self sense or consciousness has in this AI system. The current state are understand by the machine with self awareness. Presently, this type of AI does not exit.
Technologies of artificial intelligence
As w see that Artificial intelligence technologies market is flourishing there are variety of technology and tools in artificial intelligence. These are:
Speech Recognition: it transforms and transcribes the speech of human into the format that is useful for computer applications. Presently it is used in mobile application and interactive voice information system.
Machine learning: for the purpose of design deploy and train models into processes, applications and other machines, it provided the data, algorithm, Application program interface (API), training and development toolkit. It is widely used in application of enterprises mostly in classification or prediction (admin, 2017).
Natural Language Generation: this tool produced text from the data of computer. It is currently used in report generation, summarizing insights of business intelligence and customer service.
Virtual agent: virtual agent is the online representative of customer service. It is a basically virtual character of artificial agent which is animated. It performed by nonverbal behavior and responds the quest5ion of users and conversation with uses intelligently.
Deep learning Program:  neural network of artificial consisted by the machine learning which special type with several abstraction layer.

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