摘要：Human parsing is a fundamental task aimed at segmenting human images into distinct body parts and holds vast potential applications. Nowadays, the advancement of image-capturing devices has led to a growing number of high-resolution human images. Receptive field, details loss and memory usage are a triplet of contradictions in high-resolution scenarios. Existing human parsing methods designed for low-resolution inputs struggle to process high-resolution images efficiently due to their massive demands for computation and memory. Some methods save resources by overwhelmingly downsampling or encoding high-resolution inputs at the cost of poor performance on details. To resolve the issues above, we propose the Bilateral Edge-Perceiving Network (BiEPNet), consisting of a resources-friendly semantic-perceiving branch to acquire sufficient global information and a simple yet effective edge-perceiving branch used to refine details. The attention mechanism is utilized to simultaneously enhance the perception of context and details, leading to better performance on the boundary regions. To verify the effectiveness of BiEPNet, we contribute a high-resolution human parsing dataset, Human4K, containing 4,000 images with more than five million pixels. Extensive experiments on Human4K demonstrate that our method outperforms state-of-the-art methods while maintaining memory efficiency.
摘要： Most research and applications on natural language still concentrate on its superficial features and structures. However, natural language is essentially a way of encoding information and knowledge. Thus, the focus should be on what is encoded and how it is encoded. In line with this, we suggest a database-based approach for natural language processing that emulates the encoding of information and knowledge to build models. Based on these models, 1) generating sentences becomes akin to reading data from the models (or databases) and encoding it following some rules; 2) understanding sentences involves decoding rules and a series of boolean operations on the databases; 3) learning can be accomplished by writing on the databases. Our method closely mirrors how the human brain processes information, offering excellent interpretability and expandability.
摘要：Purpose/significance ChatGPT is a chatbot program developed by OpenAI in the United States. A dialog with ChatGPT can provide insights into the theory and practice of think tanks. Method/process Currently, GPT-3.5 offers users a free query quota of 30 queries per day. Chen Yu has engaged in a dialog with ChatGPT on a number of issues related to the theory and practice of think tanks by creating an outline for the dialog. Result/conclusion AI technology, represented by ChatGPT, offers many opportunities for the think tank industry, including enhanced research capabilities, data-driven decision-making, and improved public engagement. However, it also poses challenges related to ethics, expertise, transparency, and workforce adaptability that think tanks need to seriously address. In the age of AI, Chinese think tanks and experts need to keep up with the trend and proactively adopt the AI technology represented by ChatGPT.
摘要：Purpose/significance ChatGPT is a chatbot program developed by OpenAI in the United States. Conversations with ChatGPT can shed light on "Dialogue of Civilizations" in the age of AI. Method/process Currently, GPT-3.5 offers users 30 free query credits per day. By creating an outline for the conversation, Chen Yu engaged in a dialog with ChatGPT on various issues of "Dialogue of Civilizations". Result/conclusion Today, the "Standard of Civilization" has long been abandoned, and the "Clash of Civilizations" has been widely criticized. In the era of AI, the AI technology represented by ChatGPT can help promote the "Dialogue of Civilizations", help realize real-time communication between people of different cultural backgrounds, enhance the understanding and appreciation of different civilizations, and identify and alleviate prejudices in the dialogue of civilizations. At the same time, the AI technology represented by ChatGPT can also help promote "Dialogue within Civilizations" and play a positive role in resolving civil conflicts, promoting the integration of immigrants, protecting the voices of vulnerable groups, giving full play to the unique value of women, and building an age-friendly society. However, AI technologies must be developed and used with caution and with due regard to ethical considerations, in particular to prevent AI algorithms from perpetuating prejudices and reinforcing existing inequalities.
摘要：目的/意义 ChatGPT是美国OpenAI公司研发的一种聊天机器人程序。与ChatGPT进行对话，能够为AI时代的“文明的对话”提供启示。 方法/过程 目前，GPT-3.5每日向用户免费提供30次的查询额度。陈瑜通过精心设计对话提纲，与ChatGPT就“文明的对话”的若干问题展开了对话。 结果/结论 今天，“文明的标准”早已被摒弃，“文明的冲突”也受到了广泛的批评。在AI时代，以ChatGPT为代表的AI技术有助于促进“文明的对话”，帮助实现不同文化背景的人们之间的实时交流，增进对不同文明的理解和欣赏，识别和缓解文明对话中的偏见。同时，以ChatGPT为代表的AI技术也有助于促进“文明内的对话”，在解决国内冲突、促进移民融合、保护弱势群体的话语权、发挥妇女的独特价值、建设老年友好型社会等方面发挥积极作用。但是，在开发和运用AI技术时，必须谨慎从事，充分考虑伦理因素，特别是要防止AI算法延续偏见并强化现有的不平等。
摘要：Purpose/significance ChatGPT is a chatbot program developed by OpenAI in the United States. Conversations with ChatGPT can shed light on the media and communication industry in the age of AI. Method/process Currently, GPT-3.5 offers users 30 free query credits per day. By creating an outline for the conversation, Chen Yu engaged in a dialog with ChatGPT on various issues of the media and communication industry. Result/conclusion AI technology, represented by ChatGPT, has a huge impact on the media and communication industry. In the AI era, the media and communication industry should enthusiastically embrace AI technology and use it responsibly to provide a better experience for audiences. At the same time, the government, technology companies, civil society organizations, individuals, etc. should work together with the media and communication industry to solve the problems of fake news, cyber harassment, and information cocoon that may be brought about by AI technology.
摘要：目的/意义 ChatGPT是美国OpenAI公司研发的一种聊天机器人程序。与ChatGPT进行对话，能够为AI时代的新闻传播提供启示。 方法/过程 目前，GPT-3.5每日向用户免费提供30次的查询额度。陈瑜通过精心设计对话提纲，与ChatGPT就新闻传播的若干问题展开了对话。 结果/结论 以ChatGPT为代表的AI技术正在给新闻传播带来巨大的冲击。在AI时代，新闻传播行业要热情拥抱AI技术，负责任地运用AI技术，为受众提供更好的体验。同时，政府、技术公司、民间社会组织、个人等要和新闻传播行业一道，共同解决好AI技术可能带来的假新闻、网络骚扰、信息茧房等问题。
摘要：Purpose/significance Today, countries around the world are accelerating their transformation to digital government. Conversations with ChatGPT can shed light on the digital government transformation in the age of AI. Method/process Currently, GPT-3.5 offers users 30 free query credits per day. By creating an outline for the conversation, Chen Yu engaged in a dialog with ChatGPT on various issues of the digital government transformation. Result/conclusion In the age of AI, AI technologies, such as ChatGPT, have the potential to revolutionize digital government transformation by increasing efficiency, improving service delivery, and enabling data-driven decision making. While the benefits are immense, governments must also address issues of ethics, bias, and workforce adaptation to ensure responsible and inclusive AI deployments that deliver better services and work outcomes for their citizens.
摘要： 目的/意义 当前，世界各国正在加快向数字政府转型。与ChatGPT进行对话，能够为AI时代的数字政府转型提供启示。 方法/过程 目前，GPT-3.5每日向用户免费提供30次的查询额度。陈瑜通过精心设计对话提纲，与ChatGPT就数字政府转型的若干问题展开了对话。 结果/结论 在AI时代，以ChatGPT为代表的AI技术有可能彻底改变数字政府转型，提高效率，改善服务提供，并实现数据驱动的决策。虽然好处巨大，但政府也必须解决伦理、偏见和劳动力适应问题，以确保负责任和包容性的AI部署，为其公民提供更好的服务和工作成果。
摘要：Image enhancement is a common technique used to mitigate issues such as severe noise, low brightness, low contrast, and color deviation in low-light images. However, providing an optimal high-light image as a reference for low-light image enhancement tasks is impossible, which makes the learning process more difficult than other image processing tasks. As a result, although several low-light image enhancement methods have been proposed, most of them are either too complex or insufficient in addressing all the issues in low-light images. In this paper, to make the learning easier in low-light image enhancement, we introduce FLW-Net (Fast and LightWeight Network) and two relative loss functions. Specifically, we first recognize the challenges of the need for a large receptive field to obtain global contrast and the lack of an absolute reference, which limits the simplification of network structures in this task. Then, we propose an efficient global feature information extraction component and two loss functions based on relative information to overcome these challenges. Finally, we conducted comparative experiments to demonstrate the effectiveness of the proposed method, and the results confirm that the proposed method can significantly reduce the complexity of supervised low-light image enhancement networks while improving processing effect.
摘要：Purpose/significance ChatGPT is a chatbot program developed by OpenAI in the United States. Conversations with ChatGPT can shed light on the scientific research in the age of AI. Method/process Currently, ChatGPT offers users 30 free query credits per day. By creating an outline for the conversation, Chen Yu engaged in a dialog with ChatGPT on various issues of the scientific research. Result/conclusion In the AI era, the AI technology represented by ChatGPT can become a "game-changer" in scientific research. Specifically, AI technology represented by ChatGPT can achieve faster data analysis, hypothesis generation, and decision making, trigger paradigm innovation in scientific research, promote interdisciplinary research, discover new research problems and research directions, lower the "barriers to entry" to scientific research, and promote scientific popularization and knowledge dissemination. At the same time, there are a number of potential risks associated with the use of AI technology represented by ChatGPT in scientific research, including privacy or data security issues, over-reliance on AI technology, rigidity of thinking, stereotyping or even prejudice against certain genders, races, cultures, languages and ideologies, intellectual property rights, workforce adaptation, academic misconduct, and digital hegemony or AI hegemony in the English-speaking world.
摘要： 目的/意义 ChatGPT是美国OpenAI公司研发的一种聊天机器人程序。与ChatGPT进行对话，能够为AI时代的科学研究提供启示。 方法/过程 目前，ChatGPT每日向用户免费提供30次的查询额度。陈瑜通过精心设计对话提纲，与ChatGPT就科学研究的若干问题展开了对话。 结果/结论 在AI时代，以ChatGPT为代表的AI技术可能成为科学研究中的“规则改变者”。具体来说，以ChatGPT为代表的AI技术可以实现更快的数据分析、假设生成和决策制定，引发科学研究的范式创新，推动跨学科研究，发现新的研究问题和研究方向，降低科学研究的“准入障碍”，推动科学普及和知识传播等。同时，在科学研究中运用以ChatGPT为代表的AI技术可能存在一系列的潜在风险，包括隐私或数据安全问题，对AI技术的过度依赖，思维僵化，对特定性别、种族、文化、语言和意识形态的刻板印象甚至偏见，知识产权问题，劳动力适应问题，学术不端问题，以及英语世界的数字霸权或AI霸权等。
摘要：In this study, an adaptively hybrid method was proposed to improve the performance of fractal coding methods. First, we found that the range blocks with large variances (RBLVs) play a crucial role in degrading decoded images, and the effect of the remaining range blocks with small variances (RBSVs) can be ignored. Second, RBLVs were designed to be encoded in an extended domain block pool (EDBP), and the remaining RBSVs were encoded with the no-search fractal encoding method. Moreover, an effective method to adaptively divide the range blocks into the above two categories was proposed. Finally, four fractal coding methods were adopted to assess the performance of the proposed method. Experimental results show that, compared with the previous methods, the proposed method can achieve better-decoded image quality with fewer bits per pixel and fewer computations.
摘要：To predict fractal decoded image quality more efficiently, an effective decoded image quality prediction method was proposed in this study. In fractal encoding process, the dynamic range of the linear correlation coefficients (LCCs) between range blocks and their best-matched domain blocks was greatly extended by several outliers which increased uncertainty and resulted in reduced prediction accuracy. To remove the interference of outliers, we introduced the effective minimum and maximum of LCCs, which provided the effective bottom and top limits of the actual percentage of accumulated collage error (EBL-APACE and ETL-APACE), respectively. Further, when EBL-APACE reached a large percentage, the average collage error (ACER) can be estimated, and the decoded image quality can be predicted directly.
Experimental results show that compared with the previous method, the proposed method can provide higher prediction accuracy with fewer computations.
摘要：At present, the mainstream artificial intelligence generally adopts the technical path of "attention mechanism + deep learning" + "reinforcement learning". It has made great progress in the field of AIGC (Artificial Intelligence Generated Content), setting off the technical wave of big models. But in areas that need to interact with the actual environment, such as elderly care, home nanny, agricultural production, and vehicle driving, trial and error are expensive and a reinforcement learning process that requires much trial and error is difficult to achieve. Therefore, in order to achieve Artificial General Intelligence(AGI) that can be applied to any field, we need to use both existing technologies and solve the defects of existing technologies, so as to further develop the technological wave of artificial intelligence. In this paper, we analyze the limitations of the technical route of large models, and by addressing these limitations, we propose solutions, thus solving the inherent defects of large models. In this paper, we will reveal how to achieve true AGI step by step.
摘要：目前主流的人工智能，普遍采用“注意力机制 + 深度学习”+“强化学习”的技术道路。在 AIGC（Artificial Intelligence Generated Content）领域取得了长足进步，掀起了大模型的技术浪潮。但在那些需要和实际环境互动的领域，比如老人护理，家庭保姆，农业生产，车辆驾驶等领域，试错成本很高，需要大量试错的强化学习过程难以实现。所以，要想实现能适用于任何领域的通用人工智能，我们既要利用现有技术，又要解决现有技术的缺陷，从而推动人工智能的技术浪潮进一步发展。在本文中，我们分析了大模型技术路线的局限性，并针对这些局限性，提出了解决方案，从而解决了大模型的固有缺陷。在本文中，我们将揭示如何一步一步实现通用人工智能。
摘要：以 LLAMA 为代表的开源大语言模型广泛使用旋转位置编码，原始论文使用复函数推导。本文改用线性代数推导，期望更好地理解该编码方法；提出该方法的一个疑点并给出了改进建议。