The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the domain of natural language processing, which is propelling us toward the development of machines that can understand and communicate using language in a manner that closely resembles that of humans. GPT is based on the transformer architecture, a deep neural network designed for natural language processing tasks. Due to their impressive performance on natural language processing tasks and ability to effectively converse, GPT have gained significant popularity among researchers and industrial communities, making them one of the most widely used and effective models in natural language processing and related fields, which motivated to conduct this review. This review provides a detailed overview of the GPT, including its architecture, working process, training procedures, enabling technologies, and its impact on various applications. In this review, we also explored the potential challenges and limitations of a GPT. Furthermore, we discuss potential solutions and future directions. Overall, this paper aims to provide a comprehensive understanding of GPT, its enabling technologies, their impact on various applications, emerging challenges, and potential solutions. 

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

The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the domain of natural language processing, which is propelling us toward the development of machines that can understand and communicate using language in a manner that closely resembles that of humans. GPT is based on the transformer architecture, a deep neural network designed for natural language processing tasks. Due to their impressive performance on natural language processing tasks and ability to effectively converse, GPT have gained significant popularity among researchers and industrial communities, making them one of the most widely used and effective models in natural language processing and related fields, which motivated to conduct this review. This review provides a detailed overview of the GPT, including its architecture, working process, training procedures, enabling technologies, and its impact on various applications. In this review, we also explored the potential challenges and limitations of a GPT. Furthermore, we discuss potential solutions and future directions. Overall, this paper aims to provide a comprehensive understanding of GPT, enabling technologies, their impact on various applications, emerging challenges, and potential solutions.

pdf/generative-pre-trained-transformer-a-comprehensive-review-on-3n50pvmk.pdf

Generative Pre-trained Transformer: A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions

The study addresses the potential benefits for companies of adopting ChatGPT, a popular chatbot built on a large-scale transformer-based language model known as a generative pre-trained transformer (GPT). Chatbots like ChatGPT may improve customer service, handle several client inquiries at once, and save operational costs. Moreover, ChatGPT may automate regular processes like order tracking and billing, allowing human employees to focus on more complex and strategic responsibilities. Nevertheless, before deploying ChatGPT, enterprises must carefully analyze its use cases and restrictions, as well as its strengths and disadvantages. ChatGPT, for example, requires training data that is particular to the business domain and might produce erroneous and ambiguous findings. The study identifies areas of deployment of ChatGPT's possible benefits in enterprises by drawing on the literature that is currently accessible on ChatGPT, massive language models, and artificial intelligence. Then, using the PSI (Preference Selection Index) and COPRAS (Complex Proportional Assessment) approaches, potential advantages are taken into account and prioritized. By highlighting current trends and possible advantages in the industry, this editorial seeks to provide insight into the present state of employing ChatGPT in enterprises and research. ChatGPT may also learn biases from training data and create replies that reinforce those biases. As a result, enterprises must train and fine-tune ChatGPT to specific operations, set explicit boundaries and limitations for its use, and implement appropriate security measures to avoid malicious input. The study highlights the research gap in the dearth of literature by outlining ChatGPT's potential benefits for businesses, analyzing its strengths and limits, and offering insights into how organizations might use ChatGPT's capabilities to enhance their operations. 

Analyzing the potential benefits and use cases of ChatGPT as a tool for improving the efficiency and effectiveness of business operations

This research study explores the use of artificial intelligence (AI) in undergraduate assessments, specifically focusing on the ability of graduate teaching assistants (GTAs) to identify AI-generated assessments and the performance of ChatGPT, an AI model, in producing high-quality work. The study examines four guiding research questions and hypotheses related to the accuracy of GTA identification, the achievement of AI-generated work compared to student marks, the impact of GTA characteristics on identification accuracy, and the variation in identification and assessment across different subject areas. The study incorporates ten AI-generated assessments across seven classes taught by five GTAs. The findings reveal that ChatGPT consistently excelled the average student in all classes receiving 10 scores of A or higher out of 11 and receiving the top mark in 8 of the ten classes. GTAs accurately identified 50% of the AI-generated assessments, with results suggesting a potential connection between class size and GTA accuracy in identifying AI-generated work. GTAs with prior experience and familiarity with ChatGPT demonstrated higher accuracy in identifying AI-generated assessments. However, further research is needed to explore this comprehensively. This study also reviews the effectiveness of TurnItin's new AI detector, highlighting an accuracy of 92% across the ten assessments. The study highlights the adaptability of ChatGPT across different subject areas and assessment types, producing assessments that align with diverse educational contexts. In conclusion, this research study contributes to understanding the effectiveness and adaptability of AI in undergraduate assessments. It underscores the need to further explore and develop AI technologies in education. 

Graduate Instructors Navigating the AI Frontier: The Role of ChatGPT in Higher Education

The rapid progress in conversational AI has given rise to advanced language models capable of generating human- like texts. Among these models, ChatGPT and Bard, developed by OpenAI and Google AI respectively, have gained significant attention. With their wide range of functionalities, such as hu- manlike response generation, proficiency in professional exams, complex problem-solving, and more, these models have captivated interest. This paper presents a comprehensive survey that explores and compares the capabilities and features of ChatGPT and Bard. We delve into their architectures, training methodologies, performance evaluations, and limitations across various domains. Ethical considerations such as biases and potential misconduct are also examined. Our findings highlight ChatGPT’s exceptional performance, positioning it as a leading model. This survey is a vital re- source for scholars, innovators, and interested parties operating within the domain of conversational artificial intelligence, offering valuable insights for the advancement of cutting-edge language models. Join us as we uncover the potential of ChatGPT and Bard, paving the way for groundbreaking achievements in conversa- tional AI. 

ChatGPT vs. Bard: A Comparative Study

AI has become deeply ingrained in the everyday life. The matter in question does not only touch upon the mobile phones that almost everyone carries within easy reach. Today, voice assistants and smart speakers are mainly used to turn on music, turn off the lights or forecast the weather. AI chatbots are getting smarter. The use of new technologies and the general development of neural networks makes it possible to chat or answer questions, write a script, a scientific work, or program code. One of the key differences from previous GPTs is that the new version is trained to continue the text and answer questions. The answers that the bot gives surprise users around the world. Yes, there are still questions about these answers and their validity, and everyone is sure that technology needs to be improved. For a technology to become revolutionary, it must find a better, new, breakthrough application. Although no, such an application has already been invented. Farcana decided to combine the functionality of the GPT chatbot and a voice assistant. By offering players a new approach to familiarizing themselves with game mechanics and general account management, Farcana promotes its advantages over others and rapidly contributes to AI's overall development in the digital society.

Voice Assistant Integrated with Chat GPT

Regaining lost abilities via the formation of new neural pathways as a result of extensive practice and retraining is a key feature of the rehabilitation process. However, patient boredom is a big issue in rehabilitation owing to the extensive practice that is necessary. Awareness of the value of haptic (touch-enabled) interfaces in computer applications has grown because to the emergence of games with buzzing joysticks and consumer electronics with touchpads. Some forms of haptics, however, are paving the way for cutting-edge computer-based rehabilitation solutions, such as “serious games,” which are only one use of haptics’ potential to enhance clinical treatment. In this paper, we aim to review the methods and technologies of haptic feedback that are used for medical treatment and rehabilitation. Developing and innovating better haptic feedback technology has the potential to expand and improve access to virtual healthcare such as the doctor being able to “feel” a patient’s tumor from miles away by being paired with robotic devices. 

A Review of Haptic Technology Applications in Healthcare

Despite the fact that their neurobiological processes and clinical criteria are well-established, early identification remains a significant hurdle to effective, disease-modifying therapy and prolonged life quality. Gaming on computers, gaming consoles, and mobile devices has become a popular pastime and provides valuable data from several sources. High-resolution data generated when users play commercial digital games includes information on play frequency as well as performance data that reflects low-level cognitive and motor processes. In this paper, we review some methods present in the literature that is used for identification of digital biomarkers for Parkinson’s disease. We also present a machine learning method for early identification of problematic digital biomarkers for Parkinson’s disease based on tapping activity from Farcana-Mini players. However, more data is required to reach a complete evaluation of this method. This data is being collected, with their consent, from players who play Farcana-Mini. Data analysis and a full assessment of this method will be presented in future work. 

Digital Biomarker Identification for Parkinson’s Disease Using a Game-Based Approach

The Highlights are the most interesting, selling moments from video stream, which can make the viewer watch the entire video. They are like a shop window: everything that is bright and colorful goes there. Seeing them, the user can understand in advance what is inside the video. And they are more versatile than trailers: they can be made shorter or longer, embedded in different places in the user interface. The user sees a selection of highlights as soon as he gets to the website or watches a video clip on YouTube or even a section of a stream of a popular blogger/influencer. The user’s attention is immediately attracted by the most memorable shots. Naturally, it is becoming more tedious to manually create all video highlights, due to the immense amount of material that the highlights are needed for. Thus, creating an algorithm, capable of automating the process would make the process significantly simpler. Besides easing up the work, this process will pave the way to a whole set of new applications that before did not seem real. At the same time, this would be a new process where the AI would not need to be fully supervised by a human, but be capable of identifying and labeling the most interesting and attractive moments on screen. After doing a literature review on video highlight detection, this paper has utilized the model presented in the study by [1] to determine the possibility of attaining highlights from the Farcana 2.0 version Twitch video feed. 

Video Highlight of Farcana Streaming from Twitch

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Voice Assistant Integrated with Chat GPT

A Review of Haptic Technology Applications in Healthcare

Digital Biomarker Identification for Parkinson’s Disease Using a Game-Based Approach

Video Highlight of Farcana Streaming from Twitch