刘禹良1, 李鸿亮2, 白翔1, 金连文2(1.华中科技大学人工智能与自动化学院, 武汉 430074;2.华南理工大学电子与信息学院, 广州 510640)
A brief analysis of ChatGPT：historical evolution， current applications，and future prospects
Liu Yuliang1, Li Hongliang2, Bai Xiang1, Jin Lianwen2(1.School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China;2.School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640, China)
Artificial intelligence（AI）technology has been developing intensively，especially for such scenarios in relevance to its applications of 1）natural language processing，2）computer vision，3）recommendation systems，and 4）forecast analysis. AI technology has been challenging for human cognition over the past decade. In recent years，natural language processing techniques can be focused on more. ChatGPT，as a case of emerging generative AI technology，is launched in December of 2022. ChatGPT，as an advanced language model，is commonly used on the basis of its a）larger model sizes，b）advanced pre-training methods，c）faster computing resources，and d）more language processing tasks. This ChatGPT-related literature review is focused on its（1）public awareness and application status，（2）characteristics， （3）mechanisms，（4）scalability，（5）challenges and limitations，（6）future development and application prospects，and （7）improvements of GPT-4 relative to ChatGPT. Cognitive computing and AI-based ChatGPT can be as a sort of language model in terms of the Transformer architecture and Generative Pre-Training（GPT）. This GPT-trained model can be related to natural language processing，which can predict the probability distribution of the next token using a multi-layer Transformer to generate natural language text. It can be outreached by training the learned language patterns on a large corpus of text. The OpenAI’s language model has shown a significant improvement in their level of intelligence from GPT-1（117 million parameters）in 2018 to GPT-3（175 billion parameters）in 2020. The language processing and generation capabilities of GPT have been improving dramatically in terms of consistent optimization like its 1）model size，2）generative models， and 3）self-supervised learning. Thereafter，reinforcement learning-based InstructGPT is originated from Human Feedback and such probability of infeasible，untrue，and biased outputs can be significantly reduced in January 2022. In December 2022，ChatGPT is introduced as the sister model of InstructGPT. ChatGPT is not only add InstructGPT-based chat attributes，and a test version is opened to the public. The core technologies of ChatGPT can be linked to 1）reinforcement learning from human feedback（RLHF），2）supervised fine-tuning（SFT），3）instruction fine-tnning（IFT），and 4）chain-ofthought （CoT）as well. ChatGPT has attracked about 100 million active users per month after the launch of two months. In comparison，TikTok took nine months to achieve 100 million monthly active users，and Instagram took two and a half years. According to Similar Web，more than 13 million independent visitors use ChatGPT on average each day in January of 2023，which is more than twice in December of 2022. The leading US new media company Buzzfeed accurately seized the opportunity of ChatGPT and saw its stock price triple in two days. The ChatGPT-derived impact shows its potential preference for consumers. The ChatGPT can play mulitiple roles for such domain like clinics，translation，official administrations，and programming tasks. Such extensive application of ChatGPT is still to be developed. However，while ChatGPT has the potential for widespread application in various industries，it cannot be universally applied to all industries. For example，as certain industrial production processes typically rely on digitalization and do not necessitate the handling of human language，natural language processing techniques may not be required. Furthermore，various other factors，such as legal restrictions and data privacy concerns，may also impinge upon the application of natural language processing technologies within certain industries. For industries that require the processing of sensitive information，such as the healthcare industry，natural language processing technologies may need to comply with strict legal regulations to ensure data privacy and security. In addition to industry-specific reasons，it should be noted that ChatGPT has not yet achieved perfection in natural language processing tasks. In summary，as a phenomenal and technological product，AI-generated ChatGPT’s potentials are beneficial for textual and multi-modal AIGC applications to a certain extent，and it may have an impact on the a）survival of corporations，b）competition among countries，and c）entire social structure. However，the current various positive evaluations of ChatGPT can only be seen as a phenomenon of good rain after a long drought，and it cannot change the fact that ChatGPT is a questions and answers（Q&A）solution based on prior knowledge and models. It is required to be acknowledged that ChatGPT does not have its true recognition，intention，and creativity yet，and its true intelligence need to be tackled further.