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Implementation of Artificial Intelligence System and Traditional System: A Comparative Study

2019 Journal of system and management sciences  
The biggest benefits of AI systems are cost reduction, quality improvement, and faster response time.  ...  The implementation plan includes top management decision, organization and human resource, infra structure for AI system, end user support, and company strategy.  ...  To set up a effective AI learning system, it is necessary to repeat learning system to solve the problems that enterprises face with machine learning algorithms.  ... 
doi:10.33168/jsms.2019.0309 fatcat:3ukwhrawwjhbzjnxbvlffn2xea

How Machine learning is affecting financial services

Prince Ogbonna
2018 Zenodo  
Artificial intelligence (AI) and machine learning are being rapidly adopted for a range of applications in the financial services industry.  ...  Because uses of this technology in finance are in a nascent and rapidly evolving phase, and data on usage are largely unavailable, any analysis must be necessarily preliminary, and developments in this  ...  How Machine learning is affecting financial services. Artificial intelligence (AI) and machine learning are being rapidly adopted for a range of applications in the financial services industry.  ... 
doi:10.5281/zenodo.2579610 fatcat:w62o6o7aundfhd7vhjgbcr6xdu

Artificial Intelligence for Elastic Management and Orchestration of 5G Networks

David Gutierrez-Estevez, Marco Gramaglia, Antonio De Domenico, Ghina Dandachi, Sina Khatibi, Dimitris Tsolkas, Irina Balan, Andres Garcia-Saavedra, Uri Elzur, Yue Wang
2019 Zenodo  
The emergence of 5G enables a broad set of diversified and heterogeneous services with complex and potentially conflicting demands.  ...  In this paper, we propose Artificial Intelligence (AI) as a built-in architectural feature that allows the exploitation of the resource elasticity of a 5G network.  ...  The pool of parameters that feed the learning process of AI-based elastic mechanisms in this phase may be: i) requirements depicted in SLAs and service demands, ii) past measurement and statistics related  ... 
doi:10.5281/zenodo.3266981 fatcat:qzxzk6wp7rd4dowjls7pys3h5a

Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges [article]

Cheng-Xiang Wang, Marco Di Renzo, Slawomir Stańczak, Sen Wang and Erik G. Larsson
2020 arXiv   pre-print
Artificial intelligence (AI) technologies and, in particular, machine learning (ML) have the potential to efficiently solve the unstructured and seemingly intractable problems by involving large amounts  ...  Then, ML algorithms and applications to B5G networks are reviewed, followed by an overview of standard developments of applying AI/ML algorithms to B5G networks.  ...  In contrast, sophisticated ML algorithms, e.g., deep learning and probabilistic learning methods, may be able to model the highly non-linear correlations and estimate (sub-)optimal system parameters.  ... 
arXiv:2001.08159v1 fatcat:r4dx7v72e5devg3f5e5kchvnpq

Blockchain-Based Data-Preserving AI Learning Environment Model for AI Cybersecurity Systems in IoT Service Environments

Jinsu Kim, Namje Park
2020 Applied Sciences  
attack techniques, and we propose the direction of establishing a data-preserving AI system, which is a blockchain-based learning data environment model to verify the integrity of learning data.  ...  In this context, this research examines cases where AI learning data were inaccurate, in terms of cybersecurity, and the need for learning data management before machine learning through analysis of cybersecurity  ...  Proposed Method Characteristics of AI Learning Data Various types of AI technology, including deep learning, are composed of analysis and learning algorithms, computing systems, and data learning directly  ... 
doi:10.3390/app10144718 fatcat:rkc5ci5uefbujot623ovq4i62e

Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence [article]

Shuiguang Deng, Hailiang Zhao, Weijia Fang, Jianwei Yin, Schahram Dustdar, Albert Y. Zomaya
2020 arXiv   pre-print
Meanwhile, Artificial Intelligence (AI) applications are thriving with the breakthroughs in deep learning and the many improvements in hardware architectures.  ...  In this paper, we divide Edge Intelligence into AI for edge (Intelligence-enabled Edge Computing) and AI on edge (Artificial Intelligence on Edge).  ...  For example, Zhu et al. propose Learning-driven Communication, which exploits the coupling between communication and learning in edge learning systems [15] .  ... 
arXiv:1909.00560v2 fatcat:jmg3fyagazdzfbn7duiqihagea

Towards Self-learning Edge Intelligence in 6G [article]

Yong Xiao and Guangming Shi and Yingyu Li and Walid Saad and H. Vincent Poor
2020 arXiv   pre-print
In this article, we identify the key requirements and challenges of edge-native AI in 6G.  ...  We evaluate the performance of our proposed self-learning architecture in a university campus shuttle system connected via a 5G network.  ...  Human-In-The-Loop AI 1) Personalized AI: Personalized AI will play a key role in 6G to improve the decision making of AI algorithms and help machines understand better about human users preferences and  ... 
arXiv:2010.00176v1 fatcat:oavgvguokbaete3s54lrmb5kr4

EXPLORING THE POTENTIALS OF ARTIFICIAL INTELLGIENCE IN THE JUDICIARY

Oloruntoba Samson Abiodun, Akinode John Lekan
2020 International Journal of Engineering Applied Sciences and Technology  
In recent years, there has been massive progress in Artificial Intelligence (AI) with the development of machine learning, deep neural networks, natural language processing, computer vision and robotics  ...  This paper explores the potentials and efficiency of Artificial intelligence (AI) in justice delivery.  ...  MACHINE LEARNING TOOLS FOR JUDICIAR PRATICES The use of AI systems to support the work of legal practitioners has initially been observed in both public and private sectors.  ... 
doi:10.33564/ijeast.2020.v05i08.004 fatcat:hosxcyujkjekxkjeebhk5ot45q

Artificial Intelligence in Food Industry

Matthew N. O. Sadiku, OmobayodeI Fagbohungbe, Sarhan M. Musa
2020 International Journal of Engineering Research and Advanced Technology  
AI algorithms, such as machine learning and deep learning, are most commonly used to make intelligent predictions.  ...  AI-powered supply chain management systems can be used to monitor and control the activities in the entire supply chain.  ...  AI RESEARCH PROJECTS IN FOOD INDUSTRY Several food companies have incorporated machine learning, deep learning into food and beverage products and services.  ... 
doi:10.31695/ijerat.2020.3649 fatcat:g2gd3all5jailc7t65refe64wa

Special Issue on Artificial-Intelligence-Powered Edge Computing for Internet of Things

Lei Yang, Xu Chen, Samir M. Perlaza, Junshan Zhang
2020 IEEE Internet of Things Journal  
for AI-powered time-critical services in mobile-edge computing.  ...  An edge learning system based on semi-supervised learning and federated learning technologies is proposed to transform the video into useful information, providing services to IoT applications.  ... 
doi:10.1109/jiot.2020.3019948 fatcat:mogalqnhnnaqpbxb7zivzdhvry

Challenges of AI in Wireless Networks for IoT [article]

Ijaz Ahmad, Shahriar Shahabuddin, Tanesh Kumar, Erkki Harjula, Marcus Meisel, Markku Juntti, Thilo Sauter, Mika Ylianttila
2020 arXiv   pre-print
However, a number of challenges will surface while using the concepts, tools and algorithms of AI in wireless networks used by IoT.  ...  In this article, the main challenges in using AI in the wireless network infrastructure that facilitate end-to-end IoT communication are highlighted with potential generalized solution and future research  ...  Moreover, new concepts and disciplines of AI in different network systems or network services are proposed, discussed, and evaluated continuously [10] .  ... 
arXiv:2007.04705v1 fatcat:ecovbf6l6zeahjh32pvidzd2pi

The Next Decade of Telecommunications Artificial Intelligence [article]

Ye Ouyang
2021 arXiv   pre-print
operation, network AI signalling system, intelligent middle-office based BSS, intelligent customer experience management and policy control driven by BSS and OSS convergence, evolution from SLA to ELA,  ...  The paper first outlines the individual roadmaps of mobile communications and artificial intelligence in the early stage, with a concentration to review the era from 3G to 5G when AI and mobile communications  ...  and business, and AI algorithms, such as Federated Learning, Transfer Learning, etc., will help private network solve data privacy and security, data volume deficiency, etc., and AI technology is utilized  ... 
arXiv:2101.09163v6 fatcat:vojbqaqcrfdh3fcu3gjez5ypwu

Toward Native Artificial Intelligence in 6G Networks: System Design, Architectures, and Paradigms [article]

Jianjun Wu, Rongpeng Li, Xueli An, Chenghui Peng, Zhe Liu, Jon Crowcroft, Honggang Zhang
2021 arXiv   pre-print
of AI services at anytime and anywhere by anyone.  ...  In this article, we propose an end-to-end system architecture design scope for 6G, and talk about the necessity to incorporate an independent data plane and a novel intelligent plane with particular emphasis  ...  system Network function plane Data Storing Federated Learning Reinforcement Learning Model Library AI HUB Network AI Service Manager Data for AI Model Update Policy Update Policy  ... 
arXiv:2103.02823v1 fatcat:6r7v223p7bb3rkocj5vwapkopa

Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends [article]

Noman Haider, Muhammad Zeeshan Baig, Muhammad Imran
2020 arXiv   pre-print
Artificial intelligence (AI) and machine learning (ML) can play vital role in design, modelling and automation of efficient security protocols against diverse and wide range of threats.  ...  Along with the rapid evolution comes the risks, threats and vulnerabilities in the system for those who plan to exploit it.  ...  learning (DL) algorithms.  ... 
arXiv:2007.04490v1 fatcat:wlpeaoyxbjc5pgfctx2eodwrpa

AI-Driven Cybersecurity Threats to Future Networks [From the Guest Editors]

Sidi-Mohammed Senouci, Hichem Sedjelmaci, Jiajia Liu, Mubashir Husain Rehmani, Elias Bou-Harb
2020 IEEE Vehicular Technology Magazine  
To aTTack 5G services or hack The ai alGoriThms used by 5G componenTs.  ...  In the second misbehavior, attackers hack machine learning (ML) algorithms by modifying, for instance, the labels of the ML classification functions and altering the training data, causing a decrease in  ...  Turn ai inTo weapons To aTTack 5G services or hack The ai alGoriThms used by 5G componenTs.  ... 
doi:10.1109/mvt.2020.3007981 fatcat:daouv75hhzevlhfptcvtuwzflq
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