OpenAI and ChatGPT, as state-of-the-art languagemodels driven by cutting-edge artificial intelligence technology,have gained widespread adoption across diverse industries. In the realm of computer vision, these models...OpenAI and ChatGPT, as state-of-the-art languagemodels driven by cutting-edge artificial intelligence technology,have gained widespread adoption across diverse industries. In the realm of computer vision, these models havebeen employed for intricate tasks including object recognition, image generation, and image processing, leveragingtheir advanced capabilities to fuel transformative breakthroughs. Within the gaming industry, they have foundutility in crafting virtual characters and generating plots and dialogues, thereby enabling immersive and interactiveplayer experiences. Furthermore, these models have been harnessed in the realm of medical diagnosis, providinginvaluable insights and support to healthcare professionals in the realmof disease detection. The principal objectiveof this paper is to offer a comprehensive overview of OpenAI, OpenAI Gym, ChatGPT, DALL E, stable diffusion,the pre-trained clip model, and other pertinent models in various domains, encompassing CLIP Text-to-Image,education, medical imaging, computer vision, social influence, natural language processing, software development,coding assistance, and Chatbot, among others. Particular emphasis will be placed on comparative analysis andexamination of popular text-to-image and text-to-video models under diverse stimuli, shedding light on thecurrent research landscape, emerging trends, and existing challenges within the domains of OpenAI and ChatGPT.Through a rigorous literature review, this paper aims to deliver a professional and insightful overview of theadvancements, potentials, and limitations of these pioneering language models.展开更多
The distribution of material phases is crucial to determine the composite’s mechanical property.While the full structure-mechanics relationship of highly ordered material distributions can be studied with finite numb...The distribution of material phases is crucial to determine the composite’s mechanical property.While the full structure-mechanics relationship of highly ordered material distributions can be studied with finite number of cases,this relationship is difficult to be revealed for complex irregular distributions,preventing design of such material structures to meet certain mechanical requirements.The noticeable developments of artificial intelligence(AI)algorithms in material design enables to detect the hidden structure-mechanics correlations which is essential for designing composite of complex structures.It is intriguing how these tools can assist composite design.Here,we focus on the rapid generation of bicontinuous composite structures together with the stress distribution in loading.We find that generative AI,enabled through fine-tuned Low Rank Adaptation models,can be trained with a few inputs to generate both synthetic composite structures and the corresponding von Mises stress distribution.The results show that this technique is convenient in generating massive composites designs with useful mechanical information that dictate stiffness,fracture and robustness of the material with one model,and such has to be done by several different experimental or simulation tests.This research offers valuable insights for the improvement of composite design with the goal of expanding the design space and automatic screening of composite designs for improved mechanical functions.展开更多
网络内容生产迈入人工智能生成内容阶段,以ChatGPT、Stable Diffusion为代表的生成式人工智能在模型训练与内容生成方面均展现出显著的人机交互、人机协同的特征。根据生成式人工智能的特征,重新构思中文屋测试,从过程论的视角可以认定A...网络内容生产迈入人工智能生成内容阶段,以ChatGPT、Stable Diffusion为代表的生成式人工智能在模型训练与内容生成方面均展现出显著的人机交互、人机协同的特征。根据生成式人工智能的特征,重新构思中文屋测试,从过程论的视角可以认定AIGC可能具备主观论下的独创性,具有可版权性。意志能否直接决定表达不应当成为判定创作的核心要素,创作更应聚焦于独创性的贡献之上,人工智能在创作中不再是工具的角色定位,在事实上与人类合作创作作品。作品的著作权应当归属于人工智能的使用者。The production of online content has entered the stage of AI-generated content. Generative artificial intelligence, represented by ChatGPT and Stable Diffusion, exhibits significant characteristics of human-computer interaction and collaboration in both model training and content generation. Based on the features of generative artificial intelligence, rethinking the Chinese Room Test from a process-oriented perspective suggests that AIGC may possess originality under the subjective theory and thus be copyrightable. Whether or not the will directly determines expression should not be the core criterion for judging creation;instead, creation should focus more on the contribution of originality. In the process of creation, artificial intelligence is no longer positioned merely as a tool, but collaborates with humans to create works. The copyright of the work should belong to the user of the artificial intelligence.展开更多
基金the National Natural Science Foundation of China(No.62001197).
文摘OpenAI and ChatGPT, as state-of-the-art languagemodels driven by cutting-edge artificial intelligence technology,have gained widespread adoption across diverse industries. In the realm of computer vision, these models havebeen employed for intricate tasks including object recognition, image generation, and image processing, leveragingtheir advanced capabilities to fuel transformative breakthroughs. Within the gaming industry, they have foundutility in crafting virtual characters and generating plots and dialogues, thereby enabling immersive and interactiveplayer experiences. Furthermore, these models have been harnessed in the realm of medical diagnosis, providinginvaluable insights and support to healthcare professionals in the realmof disease detection. The principal objectiveof this paper is to offer a comprehensive overview of OpenAI, OpenAI Gym, ChatGPT, DALL E, stable diffusion,the pre-trained clip model, and other pertinent models in various domains, encompassing CLIP Text-to-Image,education, medical imaging, computer vision, social influence, natural language processing, software development,coding assistance, and Chatbot, among others. Particular emphasis will be placed on comparative analysis andexamination of popular text-to-image and text-to-video models under diverse stimuli, shedding light on thecurrent research landscape, emerging trends, and existing challenges within the domains of OpenAI and ChatGPT.Through a rigorous literature review, this paper aims to deliver a professional and insightful overview of theadvancements, potentials, and limitations of these pioneering language models.
基金supported by the National Science Foundation CA-REER Grant(Grant No.2145392)the startup funding at Syracuse Uni-versity for supporting the research work.
文摘The distribution of material phases is crucial to determine the composite’s mechanical property.While the full structure-mechanics relationship of highly ordered material distributions can be studied with finite number of cases,this relationship is difficult to be revealed for complex irregular distributions,preventing design of such material structures to meet certain mechanical requirements.The noticeable developments of artificial intelligence(AI)algorithms in material design enables to detect the hidden structure-mechanics correlations which is essential for designing composite of complex structures.It is intriguing how these tools can assist composite design.Here,we focus on the rapid generation of bicontinuous composite structures together with the stress distribution in loading.We find that generative AI,enabled through fine-tuned Low Rank Adaptation models,can be trained with a few inputs to generate both synthetic composite structures and the corresponding von Mises stress distribution.The results show that this technique is convenient in generating massive composites designs with useful mechanical information that dictate stiffness,fracture and robustness of the material with one model,and such has to be done by several different experimental or simulation tests.This research offers valuable insights for the improvement of composite design with the goal of expanding the design space and automatic screening of composite designs for improved mechanical functions.
文摘网络内容生产迈入人工智能生成内容阶段,以ChatGPT、Stable Diffusion为代表的生成式人工智能在模型训练与内容生成方面均展现出显著的人机交互、人机协同的特征。根据生成式人工智能的特征,重新构思中文屋测试,从过程论的视角可以认定AIGC可能具备主观论下的独创性,具有可版权性。意志能否直接决定表达不应当成为判定创作的核心要素,创作更应聚焦于独创性的贡献之上,人工智能在创作中不再是工具的角色定位,在事实上与人类合作创作作品。作品的著作权应当归属于人工智能的使用者。The production of online content has entered the stage of AI-generated content. Generative artificial intelligence, represented by ChatGPT and Stable Diffusion, exhibits significant characteristics of human-computer interaction and collaboration in both model training and content generation. Based on the features of generative artificial intelligence, rethinking the Chinese Room Test from a process-oriented perspective suggests that AIGC may possess originality under the subjective theory and thus be copyrightable. Whether or not the will directly determines expression should not be the core criterion for judging creation;instead, creation should focus more on the contribution of originality. In the process of creation, artificial intelligence is no longer positioned merely as a tool, but collaborates with humans to create works. The copyright of the work should belong to the user of the artificial intelligence.
