Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services

IEEE Communications Surveys & Tutorials, Journal Year: 2024, Volume and Issue: 26(2), P. 1127 - 1170

Published: Jan. 1, 2024

Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable diverse data using AI algorithms creatively. This survey paper focuses on the deployment of AIGC applications, e.g., ChatGPT Dall-E, at mobile edge networks, namely that provide personalized customized services in real time while maintaining user privacy. We begin by introducing background fundamentals generative models lifecycle which includes collection, training, fine-tuning, inference, product management. then discuss collaborative cloud-edge-mobile infrastructure technologies required to support enable users access networks. Furthermore, we explore AIGC-driven creative applications use cases Additionally, implementation, security, privacy challenges deploying Finally, highlight some future research directions open issues full realization

Language: Английский

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Enhancing Autonomous System Security and Resilience With Generative AI: A Comprehensive Survey

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 109470 - 109493

Published: Jan. 1, 2024

This survey explores the transformative role of Generative Artificial Intelligence (GenAI) in enhancing trustworthiness, reliability, and security autonomous systems such as Unmanned Aerial Vehicles (UAVs), self-driving cars, robotic arms. As edge robots become increasingly integrated into daily life critical infrastructure, complexity connectivity these introduce formidable challenges ensuring security, resilience, safety. GenAI advances from mere data interpretation to autonomously generating new data, proving complex, context-aware environments like robotics. Our delves impact technologies—including Adversarial Networks (GANs), Variational Autoencoders (VAEs), Transformer-based models, Large Language Models (LLMs)—on cybersecurity, decision-making, development resilient architectures. We categorize existing research highlight how technologies address operational innovate predictive maintenance, anomaly detection, adaptive threat response. comprehensive analysis distinguishes this work reviews by mapping out applications, challenges, technological advancements their on creating secure frameworks for systems. discuss significant future directions integrating within evolving landscape cyber-physical threats, underscoring potential make more adaptive, secure, efficient.

Language: Английский

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Generative artificial intelligence: a proactive and creative tool to achieve hyper-segmentation and hyper-personalization in the tourism industry

International Journal of Tourism Cities, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 29, 2024

Purpose The purpose of this paper is to explore how GenAI can help companies achieve a higher level hyper-segmentation and hyper-personalization in the tourism industry, as well show importance disruptive tool for marketing. Design/methodology/approach This used Web Science Google Scholar databases provide updated studies expert authors industry. Analysing modalities through their new challenges tourists, cities companies. Findings reveal that technology exponentially improves consumers’ segmentation personalization products services, allowing organizations create tailored content real-time. That why concept substantially focused on customer (understood segment one) his or her preferences, needs, personal motivations purchase antecedents, it encourages design services with high individual scalability performance called hyper-personalization, never before seen Indeed, contextualizing experience an important way enhance personalization. Originality/value also contributes enhancing bootstrapping literature industry because field study, its functional operability incubation stage. Moreover, viewpoint facilitate researchers successfully integrate into different travel activities without expecting utopian results. Recently, there have been no tackle methodologies

Language: Английский

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At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligence

IEEE Open Journal of the Communications Society, Journal Year: 2024, Volume and Issue: 5, P. 2433 - 2489

Published: Jan. 1, 2024

As we transition from the 5G epoch, a new horizon beckons with advent of 6G, seeking profound fusion novel communication paradigms and emerging technological trends, bringing once-futuristic visions to life along added technical intricacies. Although analytical models lay foundations offer systematic insights, have recently witnessed noticeable surge in research suggesting machine learning (ML) artificial intelligence (AI) can efficiently deal complex problems by complementing or replacing model-based approaches. The majority data-driven wireless leans heavily on discriminative AI (DAI) that requires vast real-world datasets. Unlike DAI, Generative (GenAI) pertains generative (GMs) capable discerning underlying data distribution, patterns, features input data. This makes GenAI crucial asset domain wherein is often scarce, incomplete, costly acquire, hard model comprehend. With these appealing attributes, replace supplement DAI methods various capacities. Accordingly, this combined tutorial-survey paper commences preliminaries 6G outlining candidate applications services, presenting taxonomy state-of-the-art models, exemplifying prominent use cases, elucidating multifaceted ways through which enhances DAI. Subsequently, present tutorial GMs spotlighting seminal examples such as adversarial networks, variational autoencoders, flow-based GMs, diffusion-based transformers, large language autoregressive name few. Contrary prevailing belief nascent trend, our exhaustive review approximately 120 papers demonstrates scope across core areas, including 1) physical layer design; 2) network optimization, organization, management; 3) traffic analytics; 4) cross-layer security; 5) localization & positioning. Furthermore, outline central role pioneering areas research, semantic communications, integrated sensing THz extremely antenna arrays, near-field digital twins, AI-generated content mobile edge computing AI, ML, trustworthy AI. Lastly, shed light multifarious challenges ahead, potential strategies promising remedies. Given its depth breadth, are confident tutorial-cum-survey will serve pivotal reference for researchers professionals delving into dynamic domain.

Language: Английский

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The Role of Generative Artificial Intelligence in Digital Agri-Food

Journal of Agriculture and Food Research, Journal Year: 2025, Volume and Issue: unknown, P. 101787 - 101787

Published: March 1, 2025

Language: Английский

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An Overview on Language Models: Recent Developments and Outlook

arXiv (Cornell University), Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

Language modeling studies the probability distributions over strings of texts. It is one most fundamental tasks in natural language processing (NLP). has been widely used text generation, speech recognition, machine translation, etc. Conventional models (CLMs) aim to predict linguistic sequences a causal manner, while pre-trained (PLMs) cover broader concepts and can be both sequential fine-tuning for downstream applications. PLMs have their own training paradigms (usually self-supervised) serve as foundation modern NLP systems. This overview paper provides an introduction CLMs from five aspects, i.e., units, architectures, methods, evaluation Furthermore, we discuss relationship between shed light on future directions era.

Language: Английский

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Micro‐/Nanohierarchical Surfaces for Enhanced Pool Boiling in Large‐Area Silicon Multichips

Small Structures, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

With the rising demand for data centers, need an efficient thermal management approach becomes increasingly critical. This study examines enhancement in pool boiling heat transfer on a customized multichip module, designed to mimic artificial intelligence chip layouts high‐performance computing. Experiments are conducted smooth surfaces and hierarchical structures integrating micropillars porous copper, specifically copper inverse opal (CuIO) nanowire (NW). The results demonstrate significant enhancements critical flux (CHF) coefficient (HTC) through these structures. Notably, NW‐CuIO‐integrated structure exhibits highest CHF (234 W cm −2 ), achieving 166% over silicon. HTC is more pronounced CuIO‐integrated structure; this achieves of 70.3 kW m K −1 , which represents improvement. heater layout, engineered surfaces, their synergistic effects analyzed visualization. observed inversion phenomena further underscore importance sequential activation nucleation sites improving performance. provides valuable insights into mechanisms governing offers practical guidance developing solutions centers.

Language: Английский

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Gen-Optimizer: A Generative AI Framework for Strategic Business Cost Optimization

Computers, Journal Year: 2025, Volume and Issue: 14(2), P. 59 - 59

Published: Feb. 10, 2025

Strategic cost optimization is a critical challenge for businesses aiming to maintain competitiveness in dynamic markets. This paper introduces Gen-Optimizer, Generative AI-based framework designed analyze and optimize business costs through intelligent decision support. The employs transformer-based model with over 140 million parameters, fine-tuned using diverse dataset of cost-related scenarios. By leveraging generative capabilities, Gen-Optimizer minimizes inefficiencies, automates analysis tasks, provides actionable insights decision-makers. proposed achieves exceptional performance metrics, including prediction accuracy 93.2%, precision 93.5%, recall 93.1%, an F1-score 93.3%. perplexity score 20.17 demonstrates the model’s superior language understanding abilities. was tested real-world scenarios, demonstrating its ability reduce operational by 4.11% across key functions. Furthermore, it aligns sustainability objectives, promoting resource efficiency reducing waste. highlights transformative potential AI management, paving way scalable, intelligent, cost-effective solutions.

Language: Английский

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Evaluating the Quality of AI-Generated Digital Educational Resources for University Teaching and Learning

Systems, Journal Year: 2025, Volume and Issue: 13(3), P. 174 - 174

Published: March 3, 2025

With the proliferation of artificial intelligence in education, AI-generated digital educational resources are increasingly being employed as supplements for university teaching and learning. However, this raises concerns about quality content produced. To conduct a comprehensive assessment, paper presents an evaluation index system by combining Delphi method Analytic Hierarchy Process. The initial indicators across dimensions content, expression, user technical aspects identified through systematic literature review recent research. Then, is utilized to modify according experts’ opinions two rounds questionnaire surveys. Subsequently, weight coefficients calculated using Finally, indicator evaluating developed, which comprises four twenty indicators. findings reveal that characteristics critical importance assessing resources, followed expression second most significant factor, with also recognized. Among second-level indicators, “authenticity”, “accuracy”, “legitimacy”, “relevance” accorded greater relative other proposed equips relevant stakeholders framework selecting high-quality AIGDERs steering AI tools line standards. some implications provided support selection guidance on aligning these

Language: Английский

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INT-LLPP: Lightweight in-band network-wide telemetry with low-latency and low-overhead path planning

Computer Communications, Journal Year: 2025, Volume and Issue: unknown, P. 108142 - 108142

Published: March 1, 2025

Language: Английский

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