Generative AI has the potential to change the way we do things. The chatbot is one of the most popular implementation areas. Even though companies like Google and Meta had chatbots, ChatGPT became popular as it was made publicly available. Although ChatGPT is still in the early stages of its development, it attracted the attention of people and capital groups. It has taken the public interest; people from different fields, ages, and education levels started using ChatGPT. There have been many trials with ChatGPT. It is possible to see a lot of news and shares on the Internet. The study aims to shed light on what is happening in the literature and get an insight into the user expectations of ChatGPT and Generative AI. We also give information about the competitors of ChatGPT, such as Google’s Bard AI, Claude, Meta’s Wit.ai and Tencent’s HunyuanAide. We describe technical and structural fundamentals and try to shed light on who will win the race. We also shared information about the GPT4 version of OpenAI's ChatGPT. We share the early stage due diligence and current situation analysis for all these points. We examine preprint papers and published articles. We also included striking posts on the LinkedIn platform and a compilation of various blogs and news. We also made use of ChatGPT in editing the content of these resources of this study. We can get an insight into the people's interests through their questions submitted to ChatGPT. We can also understand the capabilities of GPT3, GPT4 and also predict further enhancements.

Literature review articles are essential to summarise the related work in the selected field. However, covering all related studies takes too much time and effort. This study questions how Artificial Intelligence can be used in this process. We used ChatGPT to create a literature review article to show the stage of the OpenAI ChatGPT artificial intelligence application. As the subject, the applications of Digital Twin in the health field were chosen. Abstracts of the last three years (2020, 2021 and 2022) papers were obtained from the keyword "Digital twin in healthcare" search results on Google Scholar and paraphrased by ChatGPT. Later on, we asked ChatGPT questions. The results are promising; however, the paraphrased parts had significant matches when checked with the Ithenticate tool. This article is the first attempt to show the compilation and expression of knowledge will be accelerated with the help of artificial intelligence. We are still at the beginning of such advances. The future academic publishing process will require less human effort, which in turn will allow academics to focus on their studies. In future studies, we will monitor citations to this study to evaluate the academic validity of the content produced by the ChatGPT

Literature review articles aim to present studies in a field to researchers in a regular, systematic and meaningful way. It is often a very difficult process to reach all the studies in the field to be reviewed or to identify and evaluate the important ones. With this study, the use of Artificial Intelligence robots and moreover generative artificial intelligence in literature review processes is evaluated. Google Bard was used to detect artificial intelligence's ability to generate a literature review article. First, Bard was asked questions to write about some of the Metaverse-related topics in this article. Some of the texts in the study were generated entirely by the answers given to the questions asked by Bard. In addition, 10 articles on Metaverse published in the last three years (2021, 2022 and 2023) were collected by searching Google Scholar with the word "Metaverse". Afterwards, these studies were interpreted by Bard. Bard was told to paraphrase the summary parts of the related studies and the produced texts were shared in the study. All produced texts were checked through ithenticate and the results were evaluated. In addition, the texts were evaluated semantically. Additionally, a comparison with the capabilities of OpenAI ChatGPT is given. The results are promising; However, it was observed that the plagiarism matching rate of the paraphrased texts was higher when compared to the answers given to the questions. This article is an experiment to show that the collection and expression of knowledge can be accelerated with the help of artificial intelligence. It is considered that the relevant tools will be used more and more effectively in academic literature in the future.

Religious teachings can sometimes be complex and challenging to grasp, but chatbots can serve as effective assistants in this domain. Large Language Model (LLM) based chatbots, powered by Natural Language Processing (NLP), can connect related topics and provide well-supported responses to intricate questions, making them valuable tools for religious education. However, LLMs are prone to hallucinations as they can generate inaccurate or irrelevant information, and these can include sensitive content that could be offensive, inappropriate, or controversial. Addressing such topics without inadvertently promoting hate speech or disrespecting certain beliefs remains a significant challenge. As a solution to these issues, we introduce MufassirQAS, a system that enhances LLM accuracy and transparency using a vector database-driven Retrieval-Augmented Generation (RAG) approach. We built a dataset comprising fundamental books containing Turkish translations and interpretations of Islamic texts. This database is leveraged to answer religious inquiries while ensuring that responses remain reliable and contextually grounded. Our system also presents the relevant dataset sections alongside the LLM-generated answers, reinforcing transparency. We carefully designed system prompts to prevent harmful, offensive, or disrespectful outputs, ensuring that responses align with ethical and respectful discourse. Moreover, MufassirQAS provides supplementary details, such as source page numbers and referenced articles, to enhance credibility. To evaluate its effectiveness, we tested MufassirQAS against ChatGPT with sensitive questions, and our system demonstrated superior performance in maintaining accuracy and reliability. Future work will focus on improving accuracy and refining prompt engineering techniques to further minimize biases and ensure even more reliable responses.

Human Resources (HR) technology solutions encompass software and hardware tools designed to automate HR processes, gather, process, and analyze data, utilize it for strategic decision-making, and execute HR professionals' tasks while prioritizing security and privacy considerations. As with numerous other domains, Digital Transformation and emerging technologies have commenced integration into HR processes. These technologies are utilized by HR professionals and various stakeholders involved in HR operations. This study evaluates the utilization of Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (VR), and the Metaverse within HR management, focusing on current trends and potential opportunities. A survey was conducted to gauge HR professionals' perceptions and critiques regarding these technologies. Participants were the HR department officers, academicians who specialized in HR and staff who had courses at diverse levels about HR. This study revealed that a substantial majority of participants view integrating AI, VR, AR, and Metaverse technologies in HR processes as beneficial, particularly in enhancing training, recruitment, and performance management. In particular, ethical concerns and data security risks emerged as dominant challenges. The two-way nature of technological adoption in HR, with both positive and negative aspects, was revealed. The research contributes to the growing body of knowledge by offering statistically significant insights into how demographic factors influence perceptions of emerging technologies in HR contexts.

Sensörler, endüstri 4.0, nesnelerin interneti, makine öğrenmesi ve yapay zeka gibi kavramların son yıllarda hayatımıza girmesi ile birçok alan bu kavramlardan etkilenmiştir. Siber fiziksel sistemlerin bu kavramlar ile etkileşimi sonucunda dijital ikiz kavramı ortaya çıkmıştır. Dijital ikiz kavramı, ortaya çıkması ile birlikte birçok alanda kullanılmaya başlanmıştır. Bu modelin kullanımı özellikle karar verme süreçlerinde ciddi kazanımlar sağlamıştır. Karar verme süreçlerindeki kazanımlar her alanda katkı sağladığı gibi maliyet anlamında da değişikliklere neden olmaktadır. Bu çalışmada dijital ikiz kavramının tarihsel gelişimine değinilmiş, dijital ikizin kullanım alanları hakkında genel bilgiler verilmiştir. Bu bilgiler ışığında dijital ikiz modelinin maliyet etkisi, dolayısı ile maliyet muhasebesi penceresinden görünümü ve maliyet düşürme yöntemi olarak kullanılması değerlendirilmiştir. Türkçe literatürde yeteri kadar kaynak bulunmaması ve maliyet muhasebesi bakış açısı ile çalışmalara ışık tutmak adına bu çalışma yapılmıştır.