Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration

According to numerous reports, ChatGPT represents a significant breakthrough in the field of artificial intelligence. ChatGPT is a pre-trained AI model designed to engage in natural language conversations, utilizing sophisticated techniques from Natural Language Processing (NLP), Supervised Learning, and Reinforcement Learning to comprehend and generate text comparable to human-generated text. This article provides an overview of the training process and fundamental functionality of ChatGPT, accompanied by a preliminary review of the relevant literature. Notably, this article presents the first comprehensive literature review of this technology at the time of publication, aiming to aggregate all the available pertinent articles to facilitate further developments in the field. Ultimately, the authors aim to offer an appraisal of the technology’s potential implications on existing knowledge and technology, along with potential challenges that must be addressed.

/pdf/chatgpt-and-open-ai-models-a-preliminary-review-104m3oz9.pdf

ChatGPT and Open-AI Models: A Preliminary Review

Generative artificial intelligence (AI) is a form of AI that can autonomously generate new content, such as text, images, audio, and video. Generative AI provides innovative approaches for content production in the metaverse, filling gaps in the development of the metaverse. Products such as ChatGPT have the potential to enhance the search experience, reshape information generation and presentation methods, and become new entry points for online traffic. This is expected to significantly impact traditional search engine products, accelerating industry innovation and upgrading. This paper presents an overview of the technologies and prospective applications of generative AI in the breakthrough of metaverse technology and offers insights for increasing the effectiveness of generative AI in creating creative content. 

Generative Artificial Intelligence in the Metaverse Era

Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest and attention since its launch in November 2022. It has shown impressive performance in various domains, including passing exams and creative writing. However, challenges and concerns related to biases and trust persist. In this work, we present a comprehensive review of over 100 Scopus-indexed publications on ChatGPT, aiming to provide a taxonomy of ChatGPT research and explore its applications. We critically analyze the existing literature, identifying common approaches employed in the studies. Additionally, we investigate diverse application areas where ChatGPT has found utility, such as healthcare, marketing and financial services, software engineering, academic and scientific writing, research and education, environmental science, and natural language processing. Through examining these applications, we gain valuable insights into the potential of ChatGPT in addressing real-world challenges. We also discuss crucial issues related to ChatGPT, including biases and trustworthiness, emphasizing the need for further research and development in these areas. Furthermore, we identify potential future directions for ChatGPT research, proposing solutions to current challenges and speculating on expected advancements. By fully leveraging the capabilities of ChatGPT, we can unlock its potential across various domains, leading to advancements in conversational AI and transformative impacts in society. 

https://doi.org/10.1016/j.jksuci.2023.101675

Decoding ChatGPT: A Taxonomy of Existing Research, Current Challenges, and Possible Future Directions

Recent technological advances in synthetic data have enabled the generation of images with such high quality that human beings cannot tell the difference between real-life photographs and Artificial Intelligence (AI) generated images. Given the critical necessity of data reliability and authentication, this article proposes to enhance our ability to recognise AI-generated images through computer vision. Initially, a synthetic dataset is generated that mirrors the ten classes of the already available CIFAR-10 dataset with latent diffusion which provides a contrasting set of images for comparison to real photographs. The model is capable of generating complex visual attributes, such as photorealistic reflections in water. The two sets of data present as a binary classification problem with regard to whether the photograph is real or generated by AI. This study then proposes the use of a Convolutional Neural Network (CNN) to classify the images into two categories; Real or Fake. Following hyperparameter tuning and the training of 36 individual network topologies, the optimal approach could correctly classify the images with 92.98% accuracy. Finally, this study implements explainable AI via Gradient Class Activation Mapping to explore which features within the images are useful for classification. Interpretation reveals interesting concepts within the image, in particular, noting that the actual entity itself does not hold useful information for classification; instead, the model focuses on small visual imperfections in the background of the images. The complete dataset engineered for this study, referred to as the CIFAKE dataset, is made publicly available to the research community for future work.

pdf/cifake-image-classification-and-explainable-identification-144w9m3q.pdf

CIFAKE: Image Classification and Explainable Identification of AI-Generated Synthetic Images

ChatGPT, one of the leading Large Language Models (LLMs), has acquired linguistic capabilities such as text comprehension and logical reasoning, enabling it to engage in natural conversations with humans. As illustrated in “What Does ChatGPT Say: The DAO from Algorithmic Intelligence to Linguistic Intelligence” [1], there are three levels of intelligence: 1) Algorithmic Intelligence (AI), 2) Linguistic Intelligence (LI), 3) Imaginative Intelligence (II). ChatGPT is a powerful demonstration of Linguistic Intelligence, another milestone after AlphaGo for Algorithmic Intelligence [1]–[3]. We believe the next break-through in intelligence should be Imaginative Intelligence for artistic creation. 

/pdf/can-chatgpt-boost-artistic-creation-the-need-of-imaginative-t6b3uc83.pdf

Can ChatGPT Boost Artistic Creation: The Need of Imaginative Intelligence for Parallel Art

Could ChatGPT Imagine: Content Control for Artistic Painting Generation Via Large Language Models

Currently, the development of the foundation model, metaverse, nonfungible token (NFT), and other emerging technologies has brought profound effects on the whole art field, including art creation, dissemination, transaction, etc. However, there is no research focusing on the framework, methodologies, and applications of the human–machine collaborative creation in the metaverse era. Based on parallel theory, this article proposes a novel human–machine collaborative creation paradigm called ArtVerse, in which machines take on the roles of humans to perform creation exploration and evolution and build decentralized art organizations. Besides, the operational processes involving several key technologies are designed to achieve the proposed ArtVerse. Then, a prototype system of ArtVerse, our long-term efforts toward the human–machine collaborative painting, is presented. Finally, a new ecology of artistic creation in the metaverse era is demonstrated through the applications of the ArtVerse.

ArtVerse: A Paradigm for Parallel Human–Machine Collaborative Painting Creation in Metaverses

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Yong Dou

Author Tools

Chat about Author

Papers

Can ChatGPT Boost Artistic Creation: The Need of Imaginative Intelligence for Parallel Art

Could ChatGPT Imagine: Content Control for Artistic Painting Generation Via Large Language Models

ArtVerse: A Paradigm for Parallel Human–Machine Collaborative Painting Creation in Metaverses