potential research area for phd in artificial intelligence
DESCRIPTION
There are a huge variety of technologies and applications of AI that can be explored in the dissertation. It is significant to conduct many types of research relating to AI in the future. 4 The engagement of researchers with challenges posed due to the research in AI is unlimited. Some research topics, like the similarity and difference between analysis of the future and religious eschatology, have been well focused, with strong argumentations and reasonably obvious conclusions. Other topics such as the radical transformations that are already causing our society and our relation to one another still need a deep theological evaluation. Read more: https://bit.ly/3vwMcjy Contact: 🌐: www.tutorsindia.com 📧: [email protected] 💬(WA): +91-8754446690 🇬🇧(UK): +44-1143520021TRANSCRIPT
An Academic presentation by Dr. Nancy Agnes, Head, Technical Operations, Tutors India Group www.tutorsindia.comEmail: [email protected]
POTENTIAL RESEARCH AREAFOR PHD IN ARTIFICIALINTELLIGENCE
Abstract
Applications of Artificial Intelligence
Recent Trends in AI
Latest Topics in Artificial Intelligence
Conclusion
OUTLINE
Today's Discussion
Abstract Artificial Intelligence (AI) is focusing on one of the mostsignificant elements that could bring a remarkable change tohuman life.
Other emerging technologies include the Internet of Things(IoT), Big Data, Machine Learning.
These technologies are the unlimited and unpredictable possiblesource, and no one knows how they could change the world inthe future.
The deeper you learn about AI, the scarier you will find. We arein the most precious time of our kind.
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There is nothing that can stop us, from finding out space to getting our hands onhuman genetics.
We can modify the weather; even we are not paying attention to do it.
Even though, AI is one thing that is uncontrollable, carrying out a dissertation in AIwill enable and contribute to intelligence. 1
The reach of Artificial Intelligence is constantly growing and isused now in many domains.
Automated reasoning is the first step in artificial intelligenceprogramming.
It is a program that considers some encoded data about theworld as input and presents secondary conclusions based onthe data provided as output.
At first, this automated reasoning programming was merelyconsidered academic.
Applicationsof ArtificialIntelligence
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But today, it is used in air traffic control systems, video games, and the Mars rover. 2
In the present century, AI has been significantly used in any area of research and in allfields: Science, engineering, medicine, education, business, finance, accounting,marketing, stock market, economics, and law, among many others.
Since the intelligence of machines, the range of AI has grown tremendously withmachine learning capabilities and also has produced profound impacts ongovernments, businesses, and society.
Artificial intelligence is used in solving major issues like supply chain management,logistics, optimization of energy resources, waste management, etc.
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Also in smart production, AI can be incorporated into green manufacturing processesfor better environmental policies. 3
Next blog: Impacts of artificial intelligence in enhancing customer engagement –How AI can Improve Customer Experience Strategy
There are several factors that fueled the revolution in AI.
Most important among them is the budding of machinelearning, supported partly by resources of cloud computingresources and web-based data gathering which is extensive.
Machine learning technologies have been pushed in aforward direction by Deep learning, which is a type ofadaptive artificial neural network.
Following are the recent trends in AI.
Large-scale machine learning: Many of the machinelearning issues like supervised and unsupervised learning iswell-understood.
RecentTrends in AI
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A major effort has been made to balance existing algorithms to handle exceptionallylarge data sets.
Deep learning: The convolutional neural networks that have been trained successfullyhas benefited the most field of computer vision, and several applications like videolabeling, object recognition, activity recognition, and several others.
This technology has also benefitted many areas of insight, such as speech, audio, andnatural language processing.
Robotics: Robotic navigation has been mainly solved in static environments.
Current efforts have been made to train a robot to communicate with the world in moregeneralized and conventional ways.
Another major topic of current interest that arises in interactive environments ismanipulation.
Influence in robotics is only the beginning of the deep learning revolution.
Computer vision: The most well-known form of machine perception in computer vision.
It is the sub-field of AI which has been transformed by the rise of deep learning.
Natural Language Processing: This technology is another active area of machineperception and often coupled with automatic speech recognition. 5
1Rule-Based Expert Systems for Image Understanding:Recently several expert systems for image processing wereproposed.
The aim of rule- based expert system is to take knowledgefrom a human expert and convert this into a number ofhardcoded rules to apply to the input data.
Spatial Structure and Function in Diagnosis: Structures arerelated to object – associated visual information that remainsconstant within the period of observation.
Functions display with changes either in relation tocontemporary structures or to the background or to both.
Latest Topicsin ArtificialIntelligence
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Structures are usually visible in hierarchical spatial order, functions in both spatial andtime oriented order.
Device Modeling for a Versatile Maintenance Expert System: VMES is a device-model-based versatile maintenance expert system for the domain of digital circuits.
The objective of VMES is to interact with a maintenance technician to identify thespecific faulty components or connections of a malfunctioning circuit.
A Computational Theory of Word Recognition: Computational theory of wordrecognition has proven to be a valuable approach in developing theories of spoken-word processing.
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In this paper, we focus on a particular class of theories in which it is assumed that thespoken-word recognition process consists of two consecutive stages, with an`abstract' discrete symbolic representation at the interface between the stages.
Selection and Use of Image Features in Early Visual Processing: The visual system isconstantly bombarded with information originating from the outside world, but it isunable to process all the received information at any given time.
Machine Understanding and Data Abstraction: The main scope of this topic ismachine learning and temporal abstraction methods and their application in medicaldiagnosis.
It includes selection of methods and diagnostic domains, and also the performance orviability of approaches.
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Blockchain in healthcare: Blockchains in healthcare can be envisaged in five primaryareas: Managing electronic medical record (EMR) data.
Protection of healthcare data. Personal health record data management.
AI for sustainability: AI can be a net positive contributor to environmental sustainabilityin many industries.
Here are some examples: In agriculture, AI can transform production by bettermonitoring and managing environmental conditions and crop yields.
AI can help reduce both fertilizer and water, all while improving crop yields. 6
There are a huge variety of technologies and applications of AIthat can be explored in the dissertation.
It is significant to conduct many types of research relating to AI inthe future.
4 The engagement of researchers with challenges posed due tothe research in AI is unlimited.
Some research topics, like the similarity and difference betweenanalysis of the future and religious eschatology, have been wellfocused, with strong argumentations and reasonably obviousconclusions.
Conclusion
Contd...
Other topics such as the radical transformations that are already causing to oursociety and our relation to one another still needs a deep theological evaluation. 7
Tutorsindia offers Artificial Intelligence and Machine Learning thesis helpincludes Deep Learning, Robotics, Natural Language Processing, ReinforcementLearning, Artificial Neural Network, Expert Systems, Fuzzy Systems, ComputerVision, Biometrics, Computational Biology
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