Relevant bibliographies by topics / AI hype

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'AI hype'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "AI hype"

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Devedzic, Vladan. "Is this artificial intelligence?" Facta universitatis - series: Electronics and Energetics 33, no. 4 (2020): 499–529. http://dx.doi.org/10.2298/fuee2004499d.

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Artificial Intelligence (AI) has become one of the most frequently used terms in the technical jargon (and often in not-so-technical jargon). Recent advancements in the field of AI have certainly contributed to the AI hype, and so have numerous applications and results of using AI technology in practice. Still, just like with any other hype, the AI hype has its controversies. This paper critically examines developments in the field of AI from multiple perspectives - research, technological, social and pragmatic. Part of the controversies of the AI hype stem from the fact that people use the te
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Seifert, Franz, and Camilo Fautz. "Hype After Hype: From Bio to Nano to AI." NanoEthics 15, no. 2 (2021): 143–48. http://dx.doi.org/10.1007/s11569-021-00399-3.

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Konnelly, Lex, and Nathan Sanders. "AI hype in the classroom." Proceedings of the Linguistic Society of America 9, no. 3 (2024): 5852. http://dx.doi.org/10.3765/plsa.v9i3.5852.

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Artificial intelligence (AI) tools, especially generative tools based on large language models (LLMs), such as ChatGPT, raise critical concerns for academic integrity, for ensuring genuine assessment of student learning, and for equity. Public understanding of these tools is clouded by hype about their capabilities, as they are often treated as knowledgeable and even sentient, and thus suitable for any human task. Of particular concern for instructors is how, and how much, students rely on these tools to complete their coursework. We address some of these issues in our classrooms by reporting
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Züger, Theresa, Freia Kuper, Judith Fassbender, Anna Katzy-Reinshagen, and Irina Kühnlein. "Handling the hype: Implications of AI hype for public interest tech projects." TATuP - Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis 32, no. 3 (2023): 34–40. http://dx.doi.org/10.14512/tatup.32.3.34.

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Based on theories of expectations of technology and empirical data from expert interviews and case studies, this research article explores how actors in the field of public interest technologies relate to and within the dynamics of AI hype. On an affirmative note, practitioners and experts see the potential that AI hype can serve their own purposes, e.g., through improved funding and support structures. At the same time, public interest tech actors distance themselves from the dynamics of AI hype and criticize it explicitly. Finally, the article discusses how engagement with AI hype and its im
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Haigh, Thomas. "How the AI Boom Went Bust." Communications of the ACM 67, no. 2 (2024): 22–26. http://dx.doi.org/10.1145/3634901.

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Sheffer, Joseph. "AI in Healthcare: Less Hype, Better Data." Biomedical Instrumentation & Technology 53, no. 2 (2019): 82–83. http://dx.doi.org/10.2345/0899-8205-53.2.82.

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Di Ieva, Antonio. "AI-augmented multidisciplinary teams: hype or hope?" Lancet 394, no. 10211 (2019): 1801. http://dx.doi.org/10.1016/s0140-6736(19)32626-1.

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Yesavage, Tiffany. "AI in Clinical Trials Reality versus Hype." Genetic Engineering & Biotechnology News 43, no. 8 (2023): 36–38. http://dx.doi.org/10.1089/gen.43.08.12.

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Fox, Stephen. "Irresponsible Research and Innovation? Applying Findings from Neuroscience to Analysis of Unsustainable Hype Cycles." Sustainability 10, no. 10 (2018): 3472. http://dx.doi.org/10.3390/su10103472.

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The introduction of technological innovations is often associated with suboptimal decisions and actions during cycles of inflated expectations, disappointment, and unintended negative consequences. For brevity, these can be referred to as hype cycles. Hitherto, studies have reported hype cycles for many different technologies, and studies have proposed different methods for improving the introduction of technological innovations. Yet hype cycles persist, despite suboptimal outcomes being widely reported and despite methods being available to improve outcomes. In this communication paper, findi
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Pedersen, Isabel. "Generative AI Adoption in Postsecondary Education, AI Hype, and ChatGPT’s Launch." Open/Technology in Education, Society, and Scholarship Association Journal 4, no. 1 (2024): 1–19. http://dx.doi.org/10.18357/otessaj.2024.4.1.59.

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The rapid integration of generative artificial intelligence (AI) into postsecondary education and many other sectors resulted in a global reckoning with this new technology. This paper contributes to the study of the multifaceted influence of generative AI, with a particular focus on OpenAI's ChatGPT within academic settings during the first six months after the release in three specific ways. First, it scrutinizes the rise of ChatGPT as a transformative event construed through a study of mainstream discourses exhibiting AI hype. Second, it discusses the perceived implications of generative AI
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Dissertations / Theses on the topic "AI hype"

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Rozic, Luka, and Damon Salehi. "Uppfattning av AI i vår tid : En studie om de bakomliggande faktorerna till människors uppfattning kring AI och hur uppfattningen har förändrats över tid." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-44470.

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I det här arbetet tittar vi på artificiell intelligens genom sitt ursprung och hur tekniken har utvecklats över tiden. Eftersom begreppet diskuteras flitigt i dagens samhälle och av människors förståelse av det, vill vi klargöra vad människor faktiskt tror att artificiell intelligens är och jämföra det med dess faktiska definitioner. Eftersom artificiell intelligens har många definitioner är vårt syfte att redogöra för dessa definitioner utförligt och gå igenom AI:s historia och hur människor har uppfattat termen i generationer. Målet är att framföra en presentation av en jämförelse med hur mä
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Lin, Jiang-Tai, and 林江臺. "The implementation of assistance and labor conversion towards urban fringes group by anarchist during Japanese occupation ~ Historical action significances of Shi Chian “Ai-ai-liau” and Inagaki Fuji Hyoe “Home of humanity”." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/p9uu2j.

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碩士<br>國立清華大學<br>臺灣研究教師在職進修碩士學位班<br>104<br>During 1920’s, Taiwan intellectuals who believed anarchism, formed groups to proceed to specific book reading as well as thoughts studies in succession; nonetheless due to their intense political advocates, they all ended shortly after being formed. However the ideas about freedom, equality and abdicating class oppression remained to sustain inside the lonesome soul alliance characterizing both Inagaki Fuji Hyoe and Shi Chian, and these ideas were carried out and developed within the domain of the established Home of humanity as well as Ai-ai-liou. In
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Books on the topic "AI hype"

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Chortatos, Kōnstantinos P. To Nomikon Kathestōs tōn Nēsōn hypo to Neon tēs Thalassēs Diethnes Dikaion: Hē Hellēnikē kyriarchia epi tōn nesōn, nēsidōn kai vrachonēsidōn tou Aigaiou kai ai Tourkikai amphisvētēseis. Ekdoseis Ant. N. Sakkoula, 2001.

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Valigi, Nicolò, and Gianluca Mauro. Zero to AI: A non-technical, hype-free guide to prospering in the AI era. Manning Publications, 2020.

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Mauro, Gianluco, and Nicolo Valigi. Zero to AI: A Non-Technical, Hype-free Guide to Prospering in the AI Era. Manning Publications Co. LLC, 2020.

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Valigi, Nicolò, and Gianluca Mauro. Zero to AI: A non-technical, hype-free guide to prospering in the AI era. Manning Publications, 2020.

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Valigi, Nicolò, and Gianluca Mauro. Zero to AI: A non-technical, hype-free guide to prospering in the AI era. Manning Publications, 2020.

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Artificial Intelligence Promise vs. Peril: The Hype, Hope, and Hidden Agendas of AI. Sewell, Alan, 2023.

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Davenport, Thomas H., and Steven M. Miller. Working with AI. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14453.001.0001.

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Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, m
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Executive Guide to Artificial Intelligence: Cutting Through the Hype - How to Get the Most from AI in Your Organization. Springer International Publishing AG, 2024.

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Oberhaus, Daniel. The Silicon Shrink. The MIT Press, 2025. https://doi.org/10.7551/mitpress/14919.001.0001.

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Why the race to apply AI in psychiatry is so dangerous, and how to understand the new tech-driven psychiatric paradigm. AI psychiatrists promise to detect mental disorders with superhuman accuracy, provide affordable therapy for those who can't afford or can't access treatment, and even invent new psychiatric drugs. But the hype obscures an unnerving reality.In The Silicon Shrink, Daniel Oberhaus tells the inside story of how the quest to use AI in psychiatry has created the conditions to turn the world into an asylum. Most of these systems, he writes, have vanishingly little evidence that the
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Verdegem, Pieter, ed. AI for Everyone? Critical Perspectives. University of Westminster Press, 2021. http://dx.doi.org/10.16997/book55.

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We are entering a new era of technological determinism and solutionism in which governments and business actors are seeking data-driven change, assuming that Artificial Intelligence is now inevitable and ubiquitous. But we have not even started asking the right questions, let alone developed an understanding of the consequences. Urgently needed is debate that asks and answers fundamental questions about power. This book brings together critical interrogations of what constitutes AI, its impact and its inequalities in order to offer an analysis of what it means for AI to deliver benefits for ev
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Book chapters on the topic "AI hype"

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Ganesh, S. Valai, M. Gomathy Nayagam, V. Suresh, S. Rajakarunakaran, and B. Bensujin. "Adaptive Learning Technologies: Navigating the Road from Hype to Reality." In Multimodal Generative AI. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2355-6_4.

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Bunz, Mercedes. "The Role of Culture in the Intelligence of AI." In Edition Museum. transcript Verlag, 2023. http://dx.doi.org/10.14361/9783839467107-003.

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Artificial intelligence has received a new boost from the recent hype about large lan- guage models. However, to avoid misconceptions, it is better to speak of 'machine intelligence'. In addition to reflecting on current processes, the cultural sector can benefit from very specific machine learning approaches to transfer literary me- thods such as 'distant readings' and find new connections in cultural data. In light of resource and exploitation problems, what is needed is a 'critical technical practice' (Agre) that brings together various actors, productively engages with AI's own logics and
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Marciniak, Ruth. "Hype or Reality: AI as a Disruptor of Fashion Retail." In Fashion Marketing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82571-2_11.

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Liikkanen, Lassi A. "It AIn’t Nuttin’ New – Interaction Design Practice After the AI Hype." In Human-Computer Interaction – INTERACT 2019. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29390-1_45.

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Polfuß, Jonas. "Navigating the AI Hype: Perceptions and Opportunities in German SME Marketing Applications." In Springer Proceedings in Business and Economics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88052-0_32.

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Aliferis, Constantin, and Gyorgy Simon. "Lessons Learned from Historical Failures, Limitations and Successes of AI/ML in Healthcare and the Health Sciences. Enduring Problems, and the Role of Best Practices." In Health Informatics. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-39355-6_12.

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AbstractThis chapter covers a variety of cases studies-based incidents and concepts that are valuable for identifying pitfalls, suggesting best practices and supporting their use. Examples include: the Gartner hype cycle; the infamous “AI winters”; limitations of early-stage knowledge representation and reasoning methods; overfitting; using methods not built for the task; over-estimating the value and potential or early and heuristic technology; developing AI disconnected with real-life needs and application contexts; over-interpreting theoretical shortcomings of one algorithm to all algorithm
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Karim, Ramin, Diego Galar, and Uday Kumar. "Hypes and Trends in Industry." In AI Factory. CRC Press, 2023. http://dx.doi.org/10.1201/9781003208686-3.

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Ziesche, Soenke, and Roman V. Yampolskiy. "Mapping the Potential AI-Driven Virtual Hyper-Personalised Ikigai Universe." In Considerations on the AI Endgame. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003565659-5.

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Turky, Ayad, Nasser R. Sabar, Simon Dunstall, and Andy Song. "Hyper-heuristic Based Local Search for Combinatorial Optimisation Problems." In AI 2018: Advances in Artificial Intelligence. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03991-2_30.

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Heule, Marijn J. H., Matti Järvisalo, and Armin Biere. "Revisiting Hyper Binary Resolution." In Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38171-3_6.

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Conference papers on the topic "AI hype"

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Ramírez Masferrer, Javier Ángel, Juan Herrera Herbert, and Roberto Arranz Revenga. "FROM HYPE TO UNDERSTANDING: EDUCATIONAL STRATEGIES FOR LEVERAGING AI IN TEACHING AND LEARNING." In 19th International Technology, Education and Development Conference. IATED, 2025. https://doi.org/10.21125/inted.2025.1802.

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Ma, Jianhua, Qun Jin, Hui-Huang Hsu, et al. "Challenges and Emerging Issues for Generative AI and Hyper Intelligence." In 2024 IEEE Cyber Science and Technology Congress (CyberSciTech). IEEE, 2024. https://doi.org/10.1109/cyberscitech64112.2024.00048.

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Bisht, Ruby, and Amit Kumar Uniyal. "The Future of Job Satisfaction in a Hyper-Connected World: AI and IoT Perspectives." In 2024 8th International Conference on Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2024. https://doi.org/10.1109/iceca63461.2024.10801128.

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Sarode, Aditi, Arundhati Rothe, Ashiya Thakur, Aditya Chikte, and Snehlata Wankhade. "Gen AI Solution for Enhancing Hyper-Personalized Automotive Sales Proposal based on Customer Requirements." In 2025 4th OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 5.0. IEEE, 2025. https://doi.org/10.1109/otcon65728.2025.11071124.

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Kalra, Rishi, Zekun Wu, Ayesha Gulley, et al. "HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications." In Proceedings of the 1st Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual (CustomNLP4U). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.customnlp4u-1.18.

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Patil, Shalmali, Aparna Bhat, Nilesh Jain, and Vishal Javalkar. "Integrating Research on AI-Driven Hyper-Personalization: A Review and Framework for Scalable Social Media Campaigns." In 2025 International Conference on Pervasive Computational Technologies (ICPCT). IEEE, 2025. https://doi.org/10.1109/icpct64145.2025.10940951.

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Kalra, Rishi, Zekun Wu, Ayesha Gulley, et al. "HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications." In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track). Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.naacl-industry.79.

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Asha, V., Yagateela Pandu Rangaiah, Ginni Nijhawan, Anurag Shrivastava, G. V. V Satyanarayana, and Ali Albawi. "Exploring the Intricacies of Network Security in a Hyper-Connected World with a Focus on Encryption, Firewalls, and Intrusion Detection Systems." In 2024 1st International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI). IEEE, 2024. https://doi.org/10.1109/icscai61790.2024.10866847.

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Podgorelec, Vili, Iztok Fister, and Grega Vrbančič. "Towards Green AI by Reducing Training Effort of Recurrent Neural Networks Using Hyper-Parameter Optimization with Dynamic Stopping Criteria." In 2024 IEEE 22nd Jubilee International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2024. http://dx.doi.org/10.1109/sisy62279.2024.10737555.

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Mattmann, Chris A., and Daniel Broderick. "AI Hype versus Reality - Will It Work for You?" In 2024 IEEE Aerospace Conference. IEEE, 2024. http://dx.doi.org/10.1109/aero58975.2024.10521287.

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Reports on the topic "AI hype"

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Gehlhaus, Diana, and Ines Pancorbo. U.S. Demand for AI Certifications: Promise or Hype? Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20210001.

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This issue brief explores whether artificial intelligence and AI-related certifications serve as potential pathways to enter the U.S. AI workforce. The authors find that according to U.S. AI occupation job postings data over 2010–2020, there is little demand from employers for AI and AI-related certifications. From this perspective, such certifications appear to present more hype than promise.
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Nguyen, Aiha, and Alexandra Mateescu. Generative AI's Labor Impact. Data & Society Research Institute, 2024. https://doi.org/10.69985/gksj7804.

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As AI companies perpetuate the rhetoric that generative AI enhances efficiency and automates away drudgery - and pursue ambitions to automate everything from customer service to medical diagnoses - it is critical that claims about the technology's capabilities do not go unchallenged. This primer integrates workers' current and material experiences into public discourse and questions promotional language about the magical, infallible, and seemingly inscrutable qualities of AI. It underscores that AI does not exist outside of industries' current economic conditions and their attendant inequaliti
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King, Wayne. Barriers to Adoption of Artificial Intelligence in Metal Additive Manufacturing. SAE International, 2025. https://doi.org/10.4271/epr2025001.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Artificial intelligence (AI) is poised to significantly impact metal additive manufacturing (AM). Understanding how one might use AI in AM is challenging because AM experts are not AI experts, nor the other way around. This document introduces AI in AM and guides researchers in accessing relevant literature. It also discusses the hype surrounding AI in AM, the rush to publish peer-reviewed papers that use AI in AM, and the resulting uneven quality of the literature. Conclusions regarding the application of AI in both lar
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Pasupuleti, Murali Krishna. AI-Driven Marketing Innovations: Personalization and Ethics in the Digital Era. National Education Services, 2025. https://doi.org/10.62311/nesx/rr625.

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Abstract: This article explores the transformative impact of artificial intelligence (AI) on digital marketing, focusing on strategies for delivering personalized content and ensuring ethical advertising. By leveraging AI, marketers can now analyze consumer behavior with precision, enabling targeted content, automated ad placement, and real-time adjustments that enhance user engagement and conversions. The Article examines foundational AI techniques, such as recommendation engines, predictive analytics, and natural language processing, which drive personalization at scale. Additionally, it add
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Liu, Tairan. Addressing Urban Traffic Congestion: A Deep Reinforcement Learning-Based Approach. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2322.

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In an innovative venture, the research team embarked on a mission to redefine urban traffic flow by introducing an automated way to manage traffic light timings. This project integrates two critical technologies, Deep Q-Networks (DQN) and Auto-encoders, into reinforcement learning, with the goal of making traffic smoother and reducing the all-too-common road congestion in simulated city environments. Deep Q-Networks (DQN) are a form of reinforcement learning algorithms that learns the best actions to take in various situations through trial and error. Auto-encoders, on the other hand, are tool
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