From Traditional Recommender Systems to GPT-Based Chatbots: A Survey of Recent Developments and Future Directions DOI Creative Commons
Tamim M. Al-Hasan, Aya Nabil Sayed, Fayçal Bensaali

и другие.

Big Data and Cognitive Computing, Год журнала: 2024, Номер 8(4), С. 36 - 36

Опубликована: Март 27, 2024

Recommender systems are a key technology for many applications, such as e-commerce, streaming media, and social media. Traditional recommender rely on collaborative filtering or content-based to make recommendations. However, these approaches have limitations, the cold start data sparsity problem. This survey paper presents an in-depth analysis of paradigm shift from conventional generative pre-trained-transformers-(GPT)-based chatbots. We highlight recent developments that leverage power GPT create interactive personalized conversational agents. By exploring natural language processing (NLP) deep learning techniques, we investigate how models can better understand user preferences provide context-aware The further evaluates advantages limitations GPT-based systems, comparing their performance with traditional methods. Additionally, discuss potential future directions, including role reinforcement in refining personalization aspect systems.

Язык: Английский

Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings DOI Creative Commons
Simone Grassini

Education Sciences, Год журнала: 2023, Номер 13(7), С. 692 - 692

Опубликована: Июль 7, 2023

Over the last decade, technological advancements, especially artificial intelligence (AI), have significantly transformed educational practices. Recently, development and adoption of Generative Pre-trained Transformers (GPT), particularly OpenAI’s ChatGPT, has sparked considerable interest. The unprecedented capabilities these models, such as generating humanlike text facilitating automated conversations, broad implications in various sectors, including education health. Despite their immense potential, concerns regarding widespread use opacity been raised within scientific community. latest version GPT series, displayed remarkable proficiency, passed US bar law exam, amassed over a million subscribers shortly after its launch. However, impact on sector elicited mixed reactions, with some educators heralding it progressive step others raising alarms potential to reduce analytical skills promote misconduct. This paper aims delve into discussions, exploring problems associated applying advanced AI models education. It builds extant literature contributes understanding how technologies reshape norms “new gold rush” era.

Язык: Английский

Процитировано

521
ChatGPT and Open-AI Models: A Preliminary Review DOI Creative Commons
Konstantinos I. Roumeliotis, Nikolaos D. Tselikas

Future Internet, Год журнала: 2023, Номер 15(6), С. 192 - 192

Опубликована: Май 26, 2023

According to numerous reports, ChatGPT represents a significant breakthrough in the field of artificial intelligence. is pre-trained AI model designed engage natural language conversations, utilizing sophisticated techniques from Natural Language Processing (NLP), Supervised Learning, and Reinforcement Learning comprehend generate text comparable human-generated text. This article provides an overview training process fundamental functionality ChatGPT, accompanied by preliminary review relevant literature. Notably, this presents first comprehensive literature technology at time publication, aiming aggregate all available pertinent articles facilitate further developments field. Ultimately, authors aim offer appraisal technology’s potential implications on existing knowledge technology, along with challenges that must be addressed.

Язык: Английский

Процитировано

352
GPT (Generative Pre-Trained Transformer)— A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions DOI Creative Commons
Gokul Yenduri,

M. Ramalingam,

G. Chemmalar Selvi

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 54608 - 54649

Опубликована: Янв. 1, 2024

The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the domain of natural language processing, which is propelling us toward development machines that can understand and communicate using manner closely resembles humans. GPT based on transformer architecture, deep neural network designed for processing tasks. Due to their impressive performance tasks ability effectively converse, have gained significant popularity among researchers industrial communities, making them one most widely used effective models related fields, motivated conduct this review. This review provides detailed overview GPT, including its working process, training procedures, enabling technologies, impact various applications. In review, we also explored potential challenges limitations GPT. Furthermore, discuss solutions future directions. Overall, paper aims provide comprehensive understanding applications, emerging challenges, solutions.

Язык: Английский

Процитировано

137
Adoption and impacts of generative artificial intelligence: Theoretical underpinnings and research agenda DOI Creative Commons
Ruchi Gupta, Kiran Nair, Mahima Mishra

и другие.

International Journal of Information Management Data Insights, Год журнала: 2024, Номер 4(1), С. 100232 - 100232

Опубликована: Март 29, 2024

Large language models (LLMs) have received considerable interest in the field of natural processing (NLP) owing to their remarkable ability generate clear, consistent, and contextually relevant materials. Among numerous LLMs, ChatGPT (Generative Pre-trained Transformer for Chatbots) is emerging as a prominent prospective tool developing conversational agents such chatbots. However, there need clear conceptual understanding ChatGPT's potential implications industry its role marketing. This study explores adoption marketing examines theories that may influence by marketers consumers, well marketers. discusses how allow more personalized engaging content, better customer experience, improved ROI. also brings challenges, including ethical considerations new skill development. future research opportunities other generative artificial intelligence technologies The goal provide insights organizations consider implementing these technologies, contribute literature on Artificial Intelligence (AI) use Generative AI

Язык: Английский

Процитировано

83
A study on ChatGPT for Industry 4.0: Background, potentials, challenges, and eventualities DOI Creative Commons
Mohd Javaid, Abid Haleem, Ravi Pratap Singh

и другие.

Journal of Economy and Technology, Год журнала: 2023, Номер 1, С. 127 - 143

Опубликована: Авг. 24, 2023

ChatGPT is an Artificial Intelligence (AI)-powered Natural Language Processing (NLP) tool that comprehends and produces text in response to given commands. It can be adopted for various requirements, like answering our inquiries, assisting us with content creation, translating languages, more. The fourth industrial revolution, called "Industry 4.0," denotes a new production age focused on automation, digitalisation, real-time connectivity of systems. help Industry 4.0 variety ways. AI-driven process optimisation poised revolutionise by enhancing productivity, quality assurance, efficiency. For developing this paper, articles ChatGPT/ AI were identified through Scopus, ScienceDirect, Google Scholar ResearchGate. progresses due the incorporation cutting-edge technology AI, Machine Learning (ML), NLP Manufacturing operations are changing. language model becoming well-known daily use because its promising applications. In framework 4.0, it promises processes assist advancement boosting business productivity This paper studies major need 4.0. Various associated features, traits versatile competencies briefed. Finally, identifies discusses significant applications very flexible efficient method creating human-machine interfaces automatically generating text, which provides proper knowledge guidance employee. Applications include chatbots, virtual assistants, automated customer care, translation, production. future, will become effective communication automating

Язык: Английский

Процитировано

79
Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects DOI Creative Commons
Muhammad Usman Hadi,

qasem al tashi,

Rizwan Qureshi

и другие.

Опубликована: Ноя. 16, 2023

<p>Within the vast expanse of computerized language processing, a revolutionary entity known as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to comprehend intricate linguistic patterns and conjure coherent contextually fitting responses. models are type artificial intelligence (AI) that have emerged powerful tools for wide range tasks, including natural processing (NLP), machine translation, question-answering. This survey paper provides comprehensive overview LLMs, their history, architecture, training methods, applications, challenges. The begins by discussing fundamental concepts generative AI architecture pre- trained transformers (GPT). It then an history evolution over time, different methods been used train them. discusses applications medical, education, finance, engineering. also how LLMs shaping future they can be solve real-world problems. challenges associated with deploying scenarios, ethical considerations, model biases, interpretability, computational resource requirements. highlights techniques enhancing robustness controllability addressing bias, fairness, generation quality issues. Finally, concludes highlighting LLM research need addressed order make more reliable useful. is intended provide researchers, practitioners, enthusiasts understanding evolution, By consolidating state-of-the-art knowledge field, this serves valuable further advancements development utilization applications. GitHub repo project available at https://github.com/anas-zafar/LLM-Survey</p>

Язык: Английский

Процитировано

64
ChatGPT in Radiology: The Advantages and Limitations of Artificial Intelligence for Medical Imaging Diagnosis DOI Open Access

Samriddhi Srivastav,

Rashi Chandrakar,

Shalvi Gupta

и другие.

Cureus, Год журнала: 2023, Номер unknown

Опубликована: Июль 6, 2023

This review article provides an overview of using artificial intelligence (AI) in radiology. It discusses the advantages and limitations ChatGPT, a large language model, for medical imaging diagnosis. ChatGPT has shown great promise improving accuracy efficiency radiological diagnoses by reducing interpretation variability errors workflow efficiency. However, there are also limitations, including need high-quality training data, ethical considerations, further research development to improve its performance usability. Despite these challenges, potential significantly impact radiology The highlights continued development, coupled with regulatory ensure that is used full patient care.

Язык: Английский

Процитировано

61
A Systematic Literature Review of Information Security in Chatbots DOI Creative Commons
Yang Jing, Yen‐Lin Chen, Lip Yee Por

и другие.

Applied Sciences, Год журнала: 2023, Номер 13(11), С. 6355 - 6355

Опубликована: Май 23, 2023

Chatbots have become increasingly popular in recent years, but they also present security risks and vulnerabilities that need to be addressed. This systematic literature review examines the existing research relating information chatbots, identifying potential threats, proposed solutions, future directions for research. The finds chatbots face various including malicious input, user profiling, contextual attacks, data breaches, solutions such as blockchain technology, end-to-end encryption, organizational controls can used mitigate these concerns. highlights importance of maintaining trust addressing privacy concerns successful adoption continued use chatbots. A taxonomy developed this provides a useful framework categorizing articles their findings. concludes by include developing more sophisticated authentication authorization mechanisms, exploring privacy-enhancing technologies, improving detection prevention among others. contributes growing body on guide practice field.

Язык: Английский

Процитировано

57
Evaluating the Sensitivity, Specificity, and Accuracy of ChatGPT-3.5, ChatGPT-4, Bing AI, and Bard Against Conventional Drug-Drug Interactions Clinical Tools DOI Creative Commons
Fahmi Y. Al-Ashwal, Mohammed Zawiah, Lobna Gharaibeh

и другие.

Drug Healthcare and Patient Safety, Год журнала: 2023, Номер Volume 15, С. 137 - 147

Опубликована: Сен. 1, 2023

AI platforms are equipped with advanced ‎algorithms that have the potential to offer a wide range of ‎applications in healthcare services. However, information about accuracy chatbots against ‎conventional drug-drug interaction tools is limited‎. This study aimed assess sensitivity, specificity, and ChatGPT-3.5, ChatGPT-4, Bing AI, Bard predicting interactions.

Язык: Английский

Процитировано

57
Harnessing GPT-4 for generation of cybersecurity GRC policies: A focus on ransomware attack mitigation DOI Creative Commons
Timothy R. McIntosh, Tong Liu, Teo Sušnjak

и другие.

Computers & Security, Год журнала: 2023, Номер 134, С. 103424 - 103424

Опубликована: Авг. 11, 2023

This study investigated the potential of Generative Pre-trained Transformers (GPTs), a state-of-the-art large language model, in generating cybersecurity policies to deter and mitigate ransomware attacks that perform data exfiltration. We compared effectiveness, efficiency, completeness, ethical compliance GPT-generated Governance, Risk Compliance (GRC) policies, with those from established security vendors government agencies, using game theory, cost-benefit analysis, coverage ratio, multi-objective optimization. Our findings demonstrated could outperform human-generated certain contexts, particularly when provided tailored input prompts. To address limitations our study, we conducted analysis thorough human moderation, prompts, inclusion legal experts. Based on these results, made recommendations for corporates considering incorporation GPT their GRC policy making.

Язык: Английский

Процитировано

51