Transforming Structural Engineering: Examining the Opportunities and Risks of ChatGPT and Other Large Language Models DOI Open Access

Rishav Pokhrel,

Sital Parajuli

International Journal on Engineering Technology, Год журнала: 2023, Номер 1(1), С. 204 - 222

Опубликована: Дек. 21, 2023

The advancements in technology, particularly the development of high-performance computing (HPC) and large language models (LLMs) like ChatGPT, can potentially transform field Structural Engineering. Use LLMs, such as offers several opportunities Engineering, including innovative design solutions, use code-based structural analysis programs by automating repetitive coding tasks, conforming to building code requirements compliance checks, storing information. critical concerns arise LLM’s regarding biases, misinformation, safety, reliability, lack domain expertise. This paper explores risks associated with using ChatGPT LLMs focusing on efficiency, accuracy, reliability. main aim study is examine limitations potential relying solely machine-generated information provide mitigation strategies overcome them. Careful management prevent harmful content, collaboration human experts for accurate results, establishing guidelines standards are obligatory measures address ethical bias, privacy, abuse. Continuous monitoring updating essential maintain accuracy relevance. While offer significant benefits responsible usage combination expertise insights vital maximizing their while mitigating ensuring safe well reliable engineering practices.

Язык: Английский

Shallow-buried subway station construction period: Comparison of intelligent early warning and optimization strategies for surface deformation risk DOI

Dukun Zhao,

Jiwen Bai, Xin Chen

и другие.

Tunnelling and Underground Space Technology, Год журнала: 2024, Номер 153, С. 105978 - 105978

Опубликована: Июль 24, 2024

Язык: Английский

Процитировано

1

Artificial Intelligence tools: Boon to Engineering Education or a threat? DOI Open Access
Rajarajan Subramanian, Sofia Vidalis

Опубликована: Янв. 30, 2024

Abstract In the middle of year 2022, a big media attention was created by introduction new version AI tool, ChatGPT chatbot. Basically, chatbot is computer program that simulates and processes human conversation (either written or spoken), allowing humans to interact with digital devices as if they were communicating real person. Even though launch not felt common public, technical circle knew about its inauguration, space flooded shocked reactions. Anyone can open type in word phrase something he/she wants know, then going spit out short long essay summary what being asked. Suppose student asked submit report an on particular topic for class, be used write report. This paper discuss details impact Engineering Education other tools. Some people argue are bring down traditional education style way disseminating subject knowledge may introduced. educators think teachers lose their jobs. Many started test limits released software. The tool able produce high-quality texts various focuses even ability respond languages (internally, machine-translated into English similar "Google Translate"). Another strength contextual querying, where remembers previous queries creates results based earlier conversation. talk pros cons using tools Education.

Язык: Английский

Процитировано

0

From Deep Learning to ChatGPT for Materials Design DOI
Mohammed Mudabbiruddin,

Amir Mosavi,

Felde Imre

и другие.

Опубликована: Апрель 4, 2024

Язык: Английский

Процитировано

0

Transforming Structural Engineering: Examining the Opportunities and Risks of ChatGPT and Other Large Language Models DOI Open Access

Rishav Pokhrel,

Sital Parajuli

International Journal on Engineering Technology, Год журнала: 2023, Номер 1(1), С. 204 - 222

Опубликована: Дек. 21, 2023

The advancements in technology, particularly the development of high-performance computing (HPC) and large language models (LLMs) like ChatGPT, can potentially transform field Structural Engineering. Use LLMs, such as offers several opportunities Engineering, including innovative design solutions, use code-based structural analysis programs by automating repetitive coding tasks, conforming to building code requirements compliance checks, storing information. critical concerns arise LLM’s regarding biases, misinformation, safety, reliability, lack domain expertise. This paper explores risks associated with using ChatGPT LLMs focusing on efficiency, accuracy, reliability. main aim study is examine limitations potential relying solely machine-generated information provide mitigation strategies overcome them. Careful management prevent harmful content, collaboration human experts for accurate results, establishing guidelines standards are obligatory measures address ethical bias, privacy, abuse. Continuous monitoring updating essential maintain accuracy relevance. While offer significant benefits responsible usage combination expertise insights vital maximizing their while mitigating ensuring safe well reliable engineering practices.

Язык: Английский

Процитировано

0