OpenAI

The integration of artificial intelligence (AI) into medical education has the potential to revolutionize the way students learn about biomedical sciences. Large language models, such as ChatGPT, can serve as virtual teaching assistants, providing students with detailed and relevant information and perhaps eventually interactive simulations. ChatGPT has the potential to increase student engagement and enhance student learning, though research is needed to confirm this. The challenges and limitat

The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of using ChatGPT in higher education, and discusses the potential risks and rewards of these tools. The paper also considers the difficulties of detecting a

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from

Abstract This article discusses OpenAI's ChatGPT, a generative pre‐trained transformer, which uses natural language processing to fulfill text‐based user requests (i.e., a “chatbot”). The history and principles behind ChatGPT and similar models are discussed. This technology is then discussed in relation to its potential impact on academia and scholarly research and publishing. ChatGPT is seen as a potential model for the automated preparation of essays and other types of scholarly manuscripts.

The OpenAI’s ChatGPT-3, or Chat Generative Pre-Trained Transformer was released in November 2022 without significant warning, and has taken higher education by storm since. The artificial intelligence (AI)-powered chatbot has caused alarm for practitioners seeking to detect authenticity of student work. Whereas some educational doomsayers predict the end of education in its current form, we propose an alternate early view. We identify in this commentary a position where educators can leverage AI

Since the launch of ChatGPT for public use, educators have expressed a variety of concerns about its integration into educational settings. This paper has been written to provide an in-depth examination of these issues and explore the potential use of ChatGPT in educational contexts. Specifically, it aims to (i) present an argument in favor of incorporating ChatGPT into education and (ii) provide educators with a set of strategies and techniques to ensure responsible and successful implementatio

Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its impressive performance. In fact, ChatGPT and other Generative AI (GAI) techniques belong to the category of Artificial Intelligence Generated Content (AIGC), which involves the creation of digital content, such as images, music, and natural language, through

The appropriate recording and communication of clinical information between clinicians and patients are of paramount importance. Recently there has been a much-needed drive to improve the information that is shared with patients.1 However, the preparation of clinical letters can be time consuming. Although there has been an increase in the use of letter templates and voice recognition systems, with the aim of improving efficiency, novel technologies such as natural language processing (NLP) and

Motivation drives most human activities, including foreign language learning, and it is affected by several intrinsic and extrinsic factors. This study investigated how ChatGPT impacts learning English. A quantitative research design was used to collect data from 80 teachers and students who had access to the ChatGPT in its very beginning phase in early 2023. The sample, selected in a non-probability sampling technique, responded to an online questionnaire. Findings showed that ChatGPT generally

ChatGPT is a generative language model tool launched by OpenAI on November 30, 2022, enabling the public to converse with a machine on a broad range of topics. In January 2023, ChatGPT reached over 100 million users, making it the fastest-growing consumer application to date. This interview with ChatGPT is part 2 of a larger interview with ChatGPT. It provides a snapshot of the current capabilities of ChatGPT and illustrates the vast potential for medical education, research, and practice but al

We introduce LLaMA, a collection of foundation language models ranging from 7B to 65B parameters. We train our models on trillions of tokens, and show that it is possible to train state-of-the-art models using publicly available datasets exclusively, without resorting to proprietary and inaccessible datasets. In particular, LLaMA-13B outperforms GPT-3 (175B) on most benchmarks, and LLaMA-65B is competitive with the best models, Chinchilla-70B and PaLM-540B. We release all our models to the resea

Abstract Artificial Intelligence (AI) technologies have been progressing constantly and being more visible in different aspects of our lives. One recent phenomenon is ChatGPT, a chatbot with a conversational artificial intelligence interface that was developed by OpenAI. As one of the most advanced artificial intelligence applications, ChatGPT has drawn much public attention across the globe. In this regard, this study examines ChatGPT in education, among early adopters, through a qualitative in

The emergence of OpenAI's ChatGPT has put intense spotlight on Generative AI (Gen-AI) systems and their possible impacts on Academic integrity. This paper provides an overview of the current arguments around ChatGPT and Academic integrity and concludes that although these technologies are capable of revolutionising academia, the way ChatGPT and other generative AI systems are used could surely undermine academic integrity. However, to ensure that the risks to academic integrity are mitigated for

While still in its infancy, ChatGPT (Generative Pretrained Transformer), introduced in November 2022, is bound to hugely impact many industries, including healthcare, medical education, biomedical research, and scientific writing. Implications of ChatGPT, that new chatbot introduced by OpenAI on academic writing, is largely unknown. In response to the Journal of Medical Science (Cureus) Turing Test - call for case reports written with the assistance of ChatGPT, we present two cases one of homocy

In this study, the author collected tweets about ChatGPT, an innovative AI chatbot, in the first month after its launch. A total of 233,914 English tweets were analyzed using the latent Dirichlet allocation (LDA) topic modeling algorithm to answer the question “what can ChatGPT do?”. The results revealed three general topics: news, technology, and reactions. The author also identified five functional domains: creative writing, essay writing, prompt writing, code writing, and answering questions.

The diagnostic accuracy of differential diagnoses generated by artificial intelligence (AI) chatbots, including the generative pretrained transformer 3 (GPT-3) chatbot (ChatGPT-3) is unknown. This study evaluated the accuracy of differential-diagnosis lists generated by ChatGPT-3 for clinical vignettes with common chief complaints. General internal medicine physicians created clinical cases, correct diagnoses, and five differential diagnoses for ten common chief complaints. The rate of correct d

While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are provided in an attempt to identify emerging themes and discuss their implications for education in the 21st century. Affordances of (using) AI in Educat

This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of ChatGPT using 23 data sets covering 8 different common NLP application tasks. We evaluate the multitask, multilingual and multi-modal aspects of ChatGPT based on these data sets and a newly designed multimodal dataset. We find that ChatGPT outperforms LLMs with zero-shot learning on most tasks and even outperforms fin

The impact of generative artificial intelligence (AI) on medical publishing practices is currently unknown. However, as our experiences underline, generative AI could have substantial ethical implications.

Generative Pretrained Transformer, often known as GPT, is an innovative kind of Artificial Intelligence (AI) which can produce writing that seems to have been written by a person. OpenAI created this AI language model called ChatGPT. It is built using the GPT architecture and is trained on a large corpus of text data to respond to natural language inquiries that resemble a person’s requirements. This technology has lots of applications in healthcare. The need for accurate and current data is one

ChatGPT is the world’s most advanced chatbot thus far. Unlike other chatbots, it can create impressive prose within seconds, and it has created much hype and doomsday predictions when it comes to student assessment in higher education and a host of other matters. ChatGPT is a state-of-the-art language model (a variant of OpenAI’s Generative Pretrained Transformer (GPT) language model) designed to generate text that can be indistinguishable from text written by humans. It can engage in conversati

The use of artificial intelligence in academia is a hot topic in the education field. The use of chatAPIs and GPT-3 in higher education has the potential to offer a range of benefits, including increased student engagement, collaboration, and accessibility. However, these tools also raise a number of challenges and concerns, particularly in relation to academic honesty and plagiarism. This paper examines the opportunities and challenges of using chatAPIs and GPT-3 in higher education, with a foc

Generative artificial intelligence (AI) is ushering in an era of potential transformation of journalism and media content. This essay considers one notable generative AI platform called ChatGPT made available to the public in 2022 for free use. ChatGPT allows users to enter text prompts and rapidly generates text responses drawn from its knowledge acquired via machine learning in engagement with the internet. This essay is coauthored by a human journalism and media professor in collaboration wit

In recent years, artificial intelligence (AI) and machine learning have been transforming the landscape of scientific research. Out of which, the chatbot technology has experienced tremendous advancements in recent years, especially with ChatGPT emerging as a notable AI language model. This comprehensive review delves into the background, applications, key challenges, and future directions of ChatGPT. We begin by exploring its origins, development, and underlying technology, before examining its

Natural language processing (NLP) has been studied in computing for decades. Recent technological advancements have led to the development of sophisticated artificial intelligence (AI) models, such as Chat Generative Pre-trained Transformer (ChatGPT). These models can perform a range of language tasks and generate human-like responses, which offers exciting prospects for academic efficiency. This manuscript aims at (i) exploring the potential benefits and threats of ChatGPT and other NLP technol

Undoubtedly, the evolution of Generative AI (GenAI) models has been the highlight of digital transformation in the year 2022. As the different GenAI models like ChatGPT and Google Bard continue to foster their complexity and capability, it’s critical to understand its consequences from a cybersecurity perspective. Several instances recently have demonstrated the use of GenAI tools in both the defensive and offensive side of cybersecurity, and focusing on the social, ethical and privacy implicati

This paper explores the academic integrity considerations of students’ use of Artificial Intelligence (AI) tools using Large Language Models (LLMs) such as ChatGPT in formal assessments. We examine the evolution of these tools, and highlight the potential ways that LLMs can support in the education of students in digital writing and beyond, including the teaching of writing and composition, the possibilities of co-creation between humans and AI, supporting EFL learners, and improving Automated W

Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, Pascale Fung. Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.

Objective: The objective of the article is to provide a comprehensive identification and understanding of the challenges and opportunities associated with the use of generative artificial intelligence (GAI) in business. This study sought to develop a conceptual framework that gathers the negative aspects of GAI development in management and economics, with a focus on ChatGPT. Research Design & Methods: The study employed a narrative and critical literature review and developed a conceptual frame

Generative Large Language Models (LLMs) such as GPT-3 are capable of generating highly fluent responses to a wide variety of user prompts. However, LLMs are known to hallucinate facts and make non-factual statements which can undermine trust in their output. Existing fact-checking approaches either require access to the output probability distribution (which may not be available for systems such as ChatGPT) or external databases that are interfaced via separate, often complex, modules. In this w

With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, a

Engineering education is constantly evolving to keep up with the latest technological developments and meet the changing needs of the engineering industry. One promising development in this field is the use of generative artificial intelligence technology, such as the ChatGPT conversational agent. ChatGPT has the potential to offer personalized and effective learning experiences by providing students with customized feedback and explanations, as well as creating realistic virtual simulations for

Abstract Background Large language models such as ChatGPT can produce increasingly realistic text, with unknown information on the accuracy and integrity of using these models in scientific writing. Methods We gathered ten research abstracts from five high impact factor medical journals (n=50) and asked ChatGPT to generate research abstracts based on their titles and journals. We evaluated the abstracts using an artificial intelligence (AI) output detector, plagiarism detector, and had blinded h

We propose a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. We crafted questions that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts. We tested GPT-3, GPT-Neo/J, GPT-2 and a T5-based model. The best model was truthful on 58%

Natural language computer applications are becoming increasingly sophisticated and, with the recent release of Generative Pre-trained Transformer 3, they could be deployed in healthcare-related contexts that have historically comprised human-to-human interaction. However, for GPT-3 and similar applications to be considered for use in health-related contexts, possibilities and pitfalls need thoughtful exploration. In this article, we briefly introduce some opportunities and cautions that would ac

As if 2020 was not a peculiar enough year, its fifth month saw the relatively quiet publication of a preprint describing the most powerful natural language processing (NLP) system to date—GPT-3 (Generative Pre-trained Transformer-3)—created by the Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this artificial intelligence

Abstract GPT-3 made the mainstream media headlines this year, generating far more interest than we’d normally expect of a technical advance in NLP. People are fascinated by its ability to produce apparently novel text that reads as if it was written by a human. But what kind of practical applications can we expect to see, and can they be trusted?

Abstract In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that uses deep learning to produce human-like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic (that is, the Turing Test), and ethical questions and show