GPT (Generative Pre-Trained Transformer)— A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 54608 - 54649

Published: Jan. 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.

Language: Английский

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Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education

Information, Journal Year: 2024, Volume and Issue: 15(10), P. 596 - 596

Published: Sept. 30, 2024

This paper presents a novel framework, artificial intelligence-enabled intelligent assistant (AIIA), for personalized and adaptive learning in higher education. The AIIA system leverages advanced AI natural language processing (NLP) techniques to create an interactive engaging platform. platform is engineered reduce cognitive load on learners by providing easy access information, facilitating knowledge assessment, delivering support tailored individual needs styles. AIIA’s capabilities include understanding responding student inquiries, generating quizzes flashcards, offering pathways. research findings have the potential significantly impact design, implementation, evaluation of AI-enabled virtual teaching assistants (VTAs) education, informing development innovative educational tools that can enhance outcomes, engagement, satisfaction. methodology, architecture, services, integration with management systems (LMSs) while discussing challenges, limitations, future directions

Language: Английский

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Effects of Generative Chatbots in Higher Education

Information, Journal Year: 2023, Volume and Issue: 14(9), P. 492 - 492

Published: Sept. 7, 2023

Learning technologies often do not meet the university requirements for learner engagement via interactivity and real-time feedback. In addition to challenge of providing personalized learning experiences students, these can increase workload instructors due maintenance updates required keep courses up-to-date. Intelligent chatbots based on generative artificial intelligence (AI) technology help overcome disadvantages by transforming pedagogical activities guiding both students interactively. this study, we explore compare main characteristics existing educational chatbots. Then, propose a new theoretical framework blended with intelligent integration enabling interact online create manage their using AI tools. The advantages proposed are as follows: (1) it provides comprehensive understanding transformative potential in education facilitates effective implementation; (2) offers holistic methodology enhance overall experience; (3) unifies applications teaching–learning within universities.

Language: Английский

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Performance of ChatGPT on the US fundamentals of engineering exam: Comprehensive assessment of proficiency and potential implications for professional environmental engineering practice

Computers and Education Artificial Intelligence, Journal Year: 2023, Volume and Issue: 5, P. 100183 - 100183

Published: Jan. 1, 2023

In recent years, advancements in artificial intelligence (AI) have led to the development of large language models like GPT-4, demonstrating potential applications various fields, including education. This study investigates feasibility and effectiveness using ChatGPT, a GPT-4 based model, achieving satisfactory performance on Fundamentals Engineering (FE) Environmental Exam. further shows significant improvement model's accuracy when answering FE exam questions through noninvasive prompt modifications, substantiating utility modification as viable approach enhance AI educational contexts. Furthermore, findings reflect remarkable improvements mathematical capabilities across successive iterations ChatGPT models, showcasing their solving complex engineering problems. Our paper also explores future research directions, emphasizing importance addressing challenges education, enhancing accessibility inclusion for diverse student populations, developing AI-resistant maintain examination integrity. By evaluating context Exam, this contributes valuable insights into limitations settings. As continues evolve, these offer foundation responsible effective integration disciplines, ultimately optimizing learning experience improving outcomes.

Language: Английский

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Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching

Informatics, Journal Year: 2024, Volume and Issue: 11(1), P. 10 - 10

Published: Feb. 25, 2024

The penetration of intelligent applications in education is rapidly increasing, posing a number questions different nature to the educational community. This paper coming analyze and outline influence artificial intelligence (AI) on teaching practice which an essential problem considering its growing utilization pervasion global scale. A bibliometric approach applied outdraw “big picture” gathered bibliographic data from scientific databases Scopus Web Science. Data relevant publications matching query “artificial teaching” over past 5 years have been researched processed through Biblioshiny R environment order establish descriptive structure production, determine impact publications, trace collaboration patterns identify key research areas emerging trends. results point out growth production lately that indicator increased interest investigated topic by researchers who mainly work collaborative teams as some them are countries institutions. identified include techniques used applications, such intelligence, machine learning, deep learning. Additionally, there focus applicable technologies like ChatGPT, learning analytics, virtual reality. also explores context application for these various settings, including teaching, higher education, active e-learning, online Based our findings, trending topics can be encapsulated terms chatbots, AI, generative emotion recognition, large language models, convolutional neural networks, decision theory. These findings offer valuable insights into current landscape interests field.

Language: Английский

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Application of Large Language Models in Developing Conversational Agents for Water Quality Education, Communication and Operations

EarthArXiv (California Digital Library), Journal Year: 2024, Volume and Issue: unknown

Published: May 1, 2024

The rapid advancement of Large Language Models (LLMs), such as ChatGPT, has opened new horizons in the field Artificial Intelligence (AI), revolutionizing way we can engage with and disseminate complex information. This paper presents an innovative application ChatGPT domain Water Quality (WQ) management, through development AI Hub. Hub encompasses a suite conversational agents, each designed to address different aspects water quality including nitrogen pollution, local issues, actionable planning for conservation. These agents utilize advanced natural language processing capabilities complemented quality-related data, provide users accurate, up-to-date, contextually relevant objective is empower communities knowledge necessary understand challenges effectively. Our comprehensive evaluation these demonstrates their proficiency delivering valuable insights, overall performance accuracy exceeding 89%. underscores potential AI-enabled platforms enhancing public understanding engagement environmental conservation efforts. By bridging gap between data awareness, sets precedent sustainable management.

Language: Английский

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Centralized Database Access: Transformer Framework and LLM/Chatbot Integration-Based Hybrid Model

Applied System Innovation, Journal Year: 2024, Volume and Issue: 7(1), P. 17 - 17

Published: Feb. 15, 2024

This paper addresses the challenges associated with centralized storage of educational materials in context a fragmented and disparate database. In response to increasing demands modern education, efficient accessible retrieval for educators students is essential. presents hybrid model based on transformer framework utilizing an API existing large language (LLM)/chatbot. integration ensures precise responses drawn from comprehensive The architecture uses mathematically defined algorithms functions that enable deep text processing through advanced word embedding methods. approach improves accuracy natural both high efficiency adaptability. Therefore, this not only provides technical solution prevalent problem but also highlights potential continued development emerging technologies education. aim create more efficient, transparent, environment. importance research lies its ability streamline material access, benefiting global scientific community contributing continuous advancement technology.

Language: Английский

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Utilizing Artificial Intelligence in Higher Education: A Systematic Review

Published: Jan. 28, 2024

Research on utilization of artificial intelligence in higher education has significantly expanded recent years. However, the existing literature this domain highlights a shortage research specific subareas, such as ChatGPT and innovative advanced tools. With growing number studies focusing education, there is need to assess what extent current body filling previously reported gap. This study aims review published within last 11 months year 2023, status direction publications these areas provide comprehensive summary that will assist scholars institutions shaping their future work education. Using systematic methodology, 295 articles Scopus database were analyzed. The findings indicate majority papers serve general overview purpose, with moderate focus generative AI, integration AI into teaching learning, prediction modes. On contrary, limited directed toward for assessment, Chatbot, support administrative processes. These highlight shift efforts from more exploration topics investigation usage tools novel sophisticated manner.

Language: Английский

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The Implementation of Multimodal Large Language Models for Hydrological Applications: A Comparative Study of GPT-4 Vision, Gemini, LLaVa, and Multimodal-GPT

Hydrology, Journal Year: 2024, Volume and Issue: 11(9), P. 148 - 148

Published: Sept. 11, 2024

Large Language Models (LLMs) combined with visual foundation models have demonstrated significant advancements, achieving intelligence levels comparable to human capabilities. This study analyzes the latest Multimodal LLMs (MLLMs), including Multimodal-GPT, GPT-4 Vision, Gemini, and LLaVa, a focus on hydrological applications such as flood management, water level monitoring, agricultural discharge, pollution management. We evaluated these MLLMs hydrology-specific tasks, testing their response generation real-time suitability in complex real-world scenarios. Prompts were designed enhance models’ inference capabilities contextual comprehension from images. Our findings reveal that Vision exceptional proficiency interpreting data, providing accurate assessments of severity quality. Additionally, showed potential various applications, drought prediction, streamflow forecasting, groundwater wetland conservation. These can optimize resource management by predicting rainfall, evaporation rates, soil moisture levels, thereby promoting sustainable practices. research provides valuable insights into advanced AI addressing challenges improving decision-making

Language: Английский

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Introducing and Evaluating the Patient Report Template for AI-Powered Nursing Handoffs

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Abstract This study evaluates the effectiveness of Patient Report Template (PRT) in addressing inefficiencies nursing workflows related to electronic health records (EHRs) and clinical decision support systems. The PRT aims streamline patient handoffs, reduce charting time, enhance direct care hours, improve safety. A survey was sent 2,118 nurses at University Iowa Health Care System order gather feedback, with 106 participants electing assess perceived usefulness components their attitudes toward integrating artificial intelligence (AI) into documentation. Participants rated sections PRT, including Profile, Review Systems, Safety, on a five-point Likert scale, most receiving high ratings for usefulness. Comfort trust AI were notably low, though respondents acknowledged potential utility AI-generated reports. findings highlight PRT’s cognitive load, information consistency during address EHR-related challenges. Future work will involve implementing real-world settings validate its & accuracy explore adaptability across specialized units. What is known Electronic systems carry burdens associated data retrieval entry, as well introduce more friction workflow. record vast; free text notes are abundant underused. While crucial continuity, handoffs often lack standardization thus prone loss safety risks. this paper adds Creation feedback template which pain points charting. Feedback from about what they would not find useful handoff report. Pathway further usability testing reports make use items report template.

Language: Английский

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