文｜雷递网 雷建平 | | | | | 报告期末表决权恢复的优先股股 | | | 持有特别表决权股 | 单位:股 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 报告期未普通股股东总数 | | | 149, 017 | 东总数(如有)(参见注8) | | 0 | 份的股东总数(如 | 0 | | | | | | | | | 有) | | | | | | | 持股 5%以上的股东或前10名股东持股情况(不含通过转融通出借股份) | | | | | | 股东性 | | 持股比 | 报告期末持股 | 报告期内增减 | 持有有限售条 | 持有无限售条件的 | 质押、标记或冻结情况 | | | 股东名称 | 质 | 例 | 数量 | 变动情况 | 件的股份数量 | 股份数量 | 股份状态 | 数量 | | 新余盈瑞世纪软件研发中心(有限合 | 境内非 | | | | | | | | | 伏) | 国有法 人 | 15. 11% | 189, 744, 943 | 0 | 0 | 189.744.943 | 不适用 | 0 | | 周亚辉 | 境内自 ...

Group 1 - The article highlights the increasing risks associated with AI technology, particularly in identity fraud and privacy breaches, emphasizing the need for personal information protection [1][2] - It provides practical guidelines for identifying and preventing AI-generated fraud, including action verification methods and voice detail analysis [2] - The importance of multi-channel identity verification is stressed, especially in sensitive transactions, to avoid falling victim to scams [2] Group 2 - The article discusses the risks posed by smart devices, such as cameras and speakers, which can become gateways for privacy breaches [3][4] - Recommendations include choosing reputable brands, using physical switches for security, setting strong passwords, and minimizing app permissions [4] - The article emphasizes the need for regular management and updates of smart device settings to enhance security [4] Group 3 - The police urge individuals to enhance their awareness of personal information security as the first line of defense [5] - In cases of suspected information leaks or fraud, it is advised to retain evidence and report to authorities promptly [5] - The article calls for collaboration between the police and the public to create a safer online environment [6]

Core Viewpoint - The article discusses the viral success of an AI-generated video featuring rabbits on a trampoline, which garnered over 500 million views on TikTok, highlighting the increasing sophistication of AI-generated content and its potential to deceive viewers [2][7][25]. Group 1: AI Video Generation - The AI-generated video was initially mistaken for real footage due to its low-resolution, mimicking night vision surveillance, which naturally obscured its flaws [28][30]. - The video’s subject matter, featuring animals in a quirky scenario, contributed to its appeal and likelihood of being shared [33][34]. - The rapid advancement of AI video generation technology has led to outputs that can closely resemble real-life footage, making it challenging for viewers to discern authenticity [35][39]. Group 2: Viewer Perception and Reactions - Many viewers were fooled by the video, with some believing it to be real surveillance footage, showcasing the public's struggle to differentiate between AI-generated and real content [14][25]. - The article notes that while most AI-generated videos can still be identified as fake, the specific characteristics of this video allowed it to bypass scrutiny [25][36]. - The phenomenon has sparked concerns about the implications of AI-generated content, particularly regarding misinformation and the ability to distinguish between real and fake [24][40]. Group 3: Technical Insights - The article speculates that the AI tool used for the video is likely Veo3, based on the physical understanding and presentation of the generated content [21]. - It mentions that the current leading AI video tools, such as Veo3 and Kling, have limitations on video length, typically not exceeding 10 seconds [42]. - The article provides tips for identifying AI-generated videos, suggesting viewers check for AI-related tags and consider the typical duration of such content [40][41].

Core Viewpoint - The article discusses the rise of AI-generated videos, particularly focusing on the use of the Veo3 model, which significantly reduces production costs and allows for the creation of viral content with minimal human input [6][46]. Group 1: AI Video Creation - The introduction of Veo3 has drastically lowered the production costs for AI videos, making it an opportune time for creators to enter this space [6]. - Most viral AI videos are generated with minimal human creativity, relying heavily on AI for concept generation and execution [6][10]. - The process of creating these videos has become almost automated, allowing for the development of video agent products [6][10]. Group 2: Analyzing Viral Videos - The article outlines a method for analyzing successful videos using tools like NotebookLM, which can dissect the structure and content of viral videos [8][9]. - Key elements of successful videos include a "Contrast Engine" that creates humor through unexpected juxtapositions, an "Authentic Format" that mimics real-life recording styles, and leveraging "Shared Knowledge" to connect with the audience [11][12][13]. Group 3: Creative Expansion - The article provides a framework for expanding video ideas by utilizing AI to generate detailed scene descriptions and dialogue based on successful formats [17][21]. - Specific templates for generating prompts for both first-person Vlog and pseudo-interview styles are included, emphasizing the importance of detailed descriptions for effective content creation [29][32]. Group 4: Video Production Process - The article describes the streamlined process for generating videos using Gemini, highlighting the ease of inputting prompts and generating content [37][40]. - Post-production involves simple editing tasks, such as merging clips and adding subtitles, which can be done using common tools like剪映 [44][45]. Group 5: Future of AI Video Production - The article predicts that as AI video production technology continues to evolve, the potential for content creators will expand exponentially, leading to a surge in viral content creation [46].

Core Viewpoint - The article discusses the transformative impact of AI-generated video content on the content industry, likening it to historical paradigm shifts in human civilization, emphasizing that AI is reconstructing the fundamental logic of content production [1][12]. Group 1: AI Video Technology - AI video technology is igniting industry imagination, with notable products like OpenAI's Sora and KuaLing 2.0 leading the charge, capable of generating near-film quality short films [3][11]. - KuaLing 2.0 stands out for its immediate applicability in content creation and commercial marketing, making it widely popular among users [3][11]. - The realism achieved by AI-generated videos is not just technical but also creates a sense of trust, marking a shift from mere novelty to commercial viability [11][12]. Group 2: Content Production Logic - The core challenge of AI video generation lies in creating believable interactions among characters, objects, and environments, requiring advancements in semantic understanding, camera language, physical actions, and emotional performances [13][14]. - The role of creators is evolving from mere editors to storytellers, as they can now generate short films with simple prompts, drastically reducing production costs and time [14][27]. - AI video production can lower costs to 5%-10% of traditional methods, making it accessible for small teams and enabling rapid content creation [14][27]. Group 3: Industry Applications - AI video is being tested across various verticals, including advertising, education, IP incubation, and e-commerce, showcasing its versatility and potential for commercial applications [16][18][22]. - In advertising, AI tools can quickly transform product concepts into visual scripts and demo videos, enhancing creative processes [16]. - In education, AI can create immersive experiences, such as virtual museums and historical reenactments, demonstrating its narrative capabilities [17][18]. Group 4: Market Trends and Models - The AI video market is beginning to differentiate between technology-driven platforms (like Sora and Luma) and tool-based platforms (like KuaLing and Runway), each with distinct commercial paths [28]. - Tool-based platforms are focusing on low-barrier access for creators and exploring subscription models and content-as-a-service (CaaS) business models [28]. - AI-generated video is positioned to become a foundational element in the content supply chain, similar to how editing software has influenced video production [28]. Group 5: Future Outlook - Despite current challenges, such as multi-character interactions and maintaining consistency in longer videos, AI video is seen as a new starting point for content creation [29]. - The future of video creation may shift from "how to shoot" to "how to imagine," emphasizing the importance of creativity and storytelling over technical execution [29].

你有没有在刷视频时，看到一些超有创意的视频竟是 AI 所做？抖音和快手"AI 视频"相关的话题浏览量 上千万。AI 视频是如何做到的？在各领域应用如何？又有哪些机遇和挑战？ 本期要点荟萃 技术拐点开启商业化进 程 B端应用的机遇与挑战 C端应用的机遇与挑战 1 2 3 分享人 | 余歆瑶 （中金公司研究部传媒行业分析师） 01 技术拐点开启商业化进程 DiTs 架构的兴起 ，是视频生成技术关键的转折点。它把 Transformer 引入扩散模型，实现了生成质 量、训练稳定性、生成速度与训练成本之间的平衡，并在语义理解、生成质量和泛化能力方面均有所突 破，给 AI 视频应用打下了基础。 当前，模型应用进入商业化探索阶段。很多厂商都推出了相关的模型，如快手可灵在今年7月开启了付 费模式，6月至12月10日，积累超过600万用户，累计生成了 6500万个视频，其付费用户可以享受优先 生成视频和更高画质视频的权限。 那么，AI视频应用有哪些机会和挑战呢？ 02 B端应用的机遇与挑战 我们先来看看B端。 在 影视行业 ，AI 视频应用颇具潜力。前期策划时，可分析剧本数据，为编剧提供灵感与建议，还能 生成概念预告片等。中 ...

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