Research (10)
ProGen2: Exploring the boundaries of protein language models
A large-scale comparison of human-written versus ChatGPT-generated essays
ChatGPT and similar generative AI models have attracted hundreds of millions of users and have become part of the public discourse. Many believe that such models will disrupt society and lead to significant changes in the education system and information generation. So far, this belief is based on either colloquial evidence or benchmarks from the owners of the models-both lack scientific rigor. We systematically assess the quality of AI-generated content through a large-scale study comparing hum
Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review
The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart cities. These strides have, in turn, impacted smart eco-cities, catalyzing ongoing improvements and driving solutions to address complex environmental challenges. This aligns with the visionary concept of smarter eco-cities, an emerging paradigm
“Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model
Open AI's ChatGPT has emerged as a popular AI language model that can engage in natural language conversations with users. Based on a qualitative research approach using semistructured interviews with 32 ChatGPT users from India, this study examined the factors influencing users' acceptance and use of ChatGPT using the unified theory of acceptance and usage of technology (UTAUT) model. The study results demonstrated that the four factors of UTAUT, along with two extended constructs, i.e. perceiv
Gender bias and stereotypes in Large Language Models
Large Language Models (LLMs) have made substantial progress in the past several months, shattering state-of-the-art benchmarks in many domains. This paper investigates LLMs’ behavior with respect to gender stereotypes, a known issue for prior models. We use a simple paradigm to test the presence of gender bias, building on but differing from WinoBias, a commonly used gender bias dataset, which is likely to be included in the training data of current LLMs. We test four recently published LLMs and
A systematic review of industrial wastewater management: Evaluating challenges and enablers
The study provides a systematic literature review (SLR) encompassing industrial wastewater management research from the past decade, examining enablers, challenges, and prevailing practices. Originating from manufacturing, energy production, and diverse industrial processes, industrial wastewater's handling is critical due to its potential to impact the environment and public health. The research aims to comprehend the current state of industrial wastewater management, pinpoint gaps, and outline
Harnessing the power of synthetic data in healthcare: innovation, application, and privacy
Data-driven decision-making in modern healthcare underpins innovation and predictive analytics in public health and clinical research. Synthetic data has shown promise in finance and economics to improve risk assessment, portfolio optimization, and algorithmic trading. However, higher stakes, potential liabilities, and healthcare practitioner distrust make clinical use of synthetic data difficult. This paper explores the potential benefits and limitations of synthetic data in the healthcare anal
Artificial intelligence ‐ driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals
Abstract This study presents a comprehensive literature review using a systematic approach to explore the role of artificial intelligence (AI) in promoting sustainable development in line with the United Nations Sustainable Development Goals (SDGs). The systematic review approach was applied to collect and analyze topics, and the literature search was conducted in two stages, encompassing 57 articles that met the research requirements. Our analysis reveals that AI's contribution to sustainabilit
A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare
Artificial intelligence (AI) is expected to improve healthcare outcomes by facilitating early diagnosis, reducing the medical administrative burden, aiding drug development, personalising medical and oncological management, monitoring healthcare parameters on an individual basis, and allowing clinicians to spend more time with their patients. In the post-pandemic world where there is a drive for efficient delivery of healthcare and manage long waiting times for patients to access care, AI has an
Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments
The United States Medical Licensing Examination (USMLE) has been a subject of performance study for artificial intelligence (AI) models. However, their performance on questions involving USMLE soft skills remains unexplored. This study aimed to evaluate ChatGPT and GPT-4 on USMLE questions involving communication skills, ethics, empathy, and professionalism. We used 80 USMLE-style questions involving soft skills, taken from the USMLE website and the AMBOSS question bank. A follow-up query was us