这些老牌平台在初始发展阶段，通常都非常慷慨地给予奖励， 毕竟要留住用户，也要留住创作者。 当下视频愈发盛行，众多老牌平台也纷纷投身其中。 爱奇艺的创作者分成计划颇为简单，我们发布视频，只要有人观看，就能获得收益。 今天接着为大家分享一个老牌平台刚入场的项目——爱奇艺的创作者分成计划， 它和搜狐的情况类似，同样都是影视剧平台，同样都是刚入局， 所以现在爱奇艺推出创作分成计划，旨在吸引更多优质创作者的加入。 在寻找副业的路上，很多人都担心要花很多钱去学习，最后还学不到东西。邻居小王就曾有过这样的经历，交了不少学费，却没什么收获。后来他偶然发 现了"和风同行"，听说这是一个公众号，里面有丰富的项目拆解教程，全部都是免D的。小王说，这里的内容很详细，就算是新手也能看懂。他按照教程 一步步操作，慢慢摸索出了门道，现在每个月都能有几千收获。其实，找副业不用花冤枉钱，像这样的免F学习平台才是真正能帮到我们的。 项目原理 说起爱奇艺，大家肯定都知晓。 许多人只是用它来看剧、追综艺，但仍有不少人不了解，爱奇艺也是能够赚钱的。 先找一个剪辑软件，能够实现 AI 成片的，例如剪映和快影。 先给大家看看他人在爱奇艺耕耘 4 个月的成 ...

别找那些复杂的副业了，今天说个简单的，剪映模板拉新。先看图，有人搞了三天，赚了1万6，是不是挺猛的？ 说白了，这事儿能赚钱，就是因为其中一个视频火了。咱们的目标，就是找到复制这个"火"的最短路径。人生苦短，必须用巧劲。 相信不少人和我一样，在寻找副业的过程中吃过亏、被割过韭菜，甚至花了不少冤枉钱。如今我找项目，基本都从"顺为网创"公众号获取，那里的教程详 细，实操性强。只要愿意动手，一个月多赚个五六千是完全可以实现的。 项目背景 这项目核心就一句话：帮剪映App拉新用户，你拿提成。你在抖音发个视频，带上剪映的模板链接。一个新人通过你的链接下载了，你挣8块钱。就这么 简单，别想复杂了。 | 任务 | 价格 | 数据周期 | 结算周期 | | --- | --- | --- | --- | | 拉新单价(8月26 日-9月30日) | ¥8 | T+4 | 周结 | 操作上，直接用"剪同款"功能就行，都是现成的模板，不用你搞什么原创。因为是抖音自家的东西，流量上也不用担心被搞。好了，背景知道就行，直接 上最快的操作步骤。 操作指南 ①开通权限 第一步，拿资格。别到处乱找，直接去推广平台，滑到下面就能看到剪映的入口 ...

Core Viewpoint - The article discusses the ethical and copyright issues surrounding AI-generated videos of deceased celebrities, particularly focusing on the case of Robin Williams and the implications of OpenAI's Sora 2.0 release, which has sparked significant controversy and backlash from family members and industry stakeholders [1][2][3]. Group 1: AI Video Generation and Controversy - The release of Sora 2.0 has led to a surge in AI-generated videos featuring Robin Williams, raising concerns about the manipulation of his image and voice without consent [1][3][5]. - Robin Williams' daughter has publicly condemned the creation of AI videos of her father, emphasizing the emotional distress it causes to the family and the disrespect it shows to his legacy [5][6]. - The rapid adoption of Sora 2.0, which reportedly surpassed one million downloads within five days, highlights the growing demand for AI-generated content, but also the challenges of regulating its use [5][6]. Group 2: Legal and Ethical Implications - The article outlines the legal framework in China regarding the posthumous rights of deceased individuals, indicating that family members can claim rights over the deceased's image and voice, which complicates the use of AI in recreating these figures [8][9]. - OpenAI has faced pressure from various stakeholders, including Hollywood unions and family members, to establish clearer boundaries regarding the use of deceased individuals' likenesses in AI-generated content [13][14]. - OpenAI has adjusted its copyright policy from an opt-out to an opt-in mechanism, allowing public figures to control the use of their likenesses in Sora-generated videos, although this does not address the rights of deceased individuals [14][15]. Group 3: Industry Response and Future Directions - The article notes that the backlash against AI-generated content is not isolated, as other companies in the industry have faced similar legal challenges and public outcry regarding copyright infringement [13][16]. - There is a call for a more structured approach to the ethical use of AI in recreating public figures, with suggestions for obtaining explicit consent from deceased individuals' estates and establishing clearer guidelines for AI platforms [9][16]. - The ongoing debate highlights the tension between artistic expression and the rights of individuals, suggesting that the industry is still in the process of finding a balance between innovation and ethical responsibility [16].

| Abstract | The coming of the digital communication era triggered significant changes of the advertising environment, which further leads to various difficulties and challenges for advertising education in universities. In the process of vigorously promoting the construction of new liberal arts in China, the digital transformation of advertising education in universities is urgently needed. It is particularly manifested in the expansion of disciplinary boundaries, the reshaping of professional theoretical ...

文 \一只呀 混沌商业研究团队 这篇文章，是 AI写的吗？ 这也许是最近很多人心中最常见的疑问。打开公众号、短视频、小红书，几乎每一条推送都像是为我们量身定 制的。这些内容不仅标题勾人、配图精致、文字流畅，甚至连语气都恰到好处。 在 AI时代，内容的生产线几乎被彻底重构。AI让自媒体的门槛坍塌，也让竞争空前激烈。有人用AI批量做 号、月入百万；有人被淹没在算法洪流里，辛苦写作却无人问津。 2025年的自媒体人已 不再需要精通每一项技能，核心工作不再是亲手写作或绘画，而是向 ChatGPT、Claude等 大模型精准地下达生产任务，向Midjourney、Stable Diffusion描述视觉需 求，再指令 Sora等视频生成工具或AI 剪辑软件完成动态呈现。 总的来说，现在的内容生产，变成了 "AI调度"。不过这绝不意味着创作变得毫无门槛。恰恰相反，旧的门槛降 低，新的壁垒随之竖起，它虽然隐蔽，却在AI时代至关重要。这一门槛意味着， AI降低了劳动门槛，却抬高 了认知门槛 。 虽然 AI参与创作不意味着作品质量低下，但对于每天被自媒体容包围的我们来说，或该去追问： 当 AI生成的 内容大量充斥于自媒体行业 ...

今天一定要给你们分享一个超棒的副业项目——手绘人生感悟视频。 这个项目堪称赚钱利器，操作简单得很，短短10分钟就能产出一条原创作品，而且可以在各大平台发布，轻松赚钱不是梦。 就拿视频号来说吧，有人凭借十几条作品，半个月的创作者分成就能轻松拿到3000多元。 | 收益明细 | | | --- | --- | | 2月18日收益结算 | 预期收益 | | 17个视频产生收益 | ¥706.75 | | 2月17日收益结算 | 预期收益 | | 18个视频产生收益 | ¥551.16 | | 2月16日收益绩 つら个初師产生收之 | 预期收益 ¥715 24 | 在寻找副业的路上，很多人都担心要花很多钱去学习，最后还学不到东西。邻居小王就曾有过这样的经历，交了不少学费，却没什么收获。后来他偶然发 现了"和风同行"，听说这是一个公众号，里面有丰富的项目拆解教程，全部都是免D的。小王说，这里的内容很详细，就算是新手也能看懂。他按照教程 一步步操作，慢慢摸索出了门道，现在每个月都能有几千收获。其实，找副业不用花冤枉钱，像这样的免F学习平台才是真正能帮到我们的。 要是做出了爆款，达到10W+的播放量、10W+的点赞量，一天 ...

说起来你们可能不信，国庆假期的第一天，我刷了一整天的短视频。 不过我刷的并不是抖音或者快手，而是OpenAI10月1日推出的新App。 这么说吧，这玩意在内容形态上看，活脱脱就是AI视频纯享版的抖音。 无论是宝可梦奶龙使出宝宝肚肚打雷的技能，硬刚赛亚人；还是山姆·奥特曼，用物理方式把谷歌Veo 3炸个稀巴烂；甚至是让Jesus直播《我的世界》，再 现造物全过程。 你能想到或者想不到的画面，都能在这儿直接生成AI视频，并通过短视频的形式在平台上分享互动。 你要是上传非AI的真人视频，反而可能会被网友们抵制。 而这App背后的更多故事，则要从10月1号凌晨说起。 是的，就在大伙刚开始享受国庆假期的时候，OpenAI偷袭了一波AI圈，在凌晨一点直播发布了他们的新模型Sora 2。 看到他们官方的演示，我只能说，我是真的分不清这花花世界到底是假是真了。 因为之前的老模型会经常扭曲物理定律，动不动就去踹两脚牛顿的棺材板。 而这一次，至少从官方的视频来看，Sora 2堪比物理特长生。无论是跳水的水花，还是翻跟头的人，毫无违和感。 0:00 / 0:05 模型在可控性方面也提升了一大波，比如一些多镜头视角转换的视频，画面已 ...

Core Viewpoint - The article emphasizes the challenges faced by AI companies in global expansion, particularly in infrastructure, talent, and business models, with a focus on the integration of high-quality large models and products for effective globalization [2][6]. Group 1: Development and Technical Route of Mureka Model - The Mureka model was initiated in 2020, leveraging existing music processing technologies and data accumulated from a music social product, Starmaker, which holds a significant market position overseas [7]. - The decision to enter the music generation field was based on the observation that the scale of music data is smaller compared to text and video data, leading to lower required investment and training resources [7]. - The company initially explored various technical routes for music generation, ultimately adopting the Diffusion Transformer (DIT) approach, which significantly improved the model's performance [9]. Group 2: Global Promotion Challenges and Non-Acquisition Growth - After developing the model, the company faced challenges in global promotion, particularly the reliance on user acquisition (UA) models, which are less effective in the AI startup landscape [11]. - Non-acquisition growth strategies include leveraging core technological breakthroughs for viral growth, SEO for user acquisition, and GEO optimization, which are essential for companies to explore beyond traditional UA methods [12][13]. Group 3: Product Judgement Standards and Market Opportunities - The article outlines two core judgments for the feasibility of To B products: they serve as "efficiency multipliers" and act as "workflow adhesives" to enhance automation [15]. - For To C products, the focus is on reducing production costs significantly, with AI music generation costing less than 0.1 RMB per song compared to traditional methods costing around 100,000 RMB [16]. - The article highlights the growing competitiveness of Chinese open-source large models, indicating that small and medium enterprises can leverage these models to build new ecosystems and tap into vast market opportunities [17].

Summary of Conference Call Records Industry Overview - The conference call focuses on the AI model landscape in China, highlighting the challenges and advancements in the domestic AI industry compared to international counterparts [1][2][4][5]. Key Points and Arguments 1. **Architecture and Innovation** - Domestic AI models heavily rely on overseas architectures like Transformer and MoE, leading to difficulties in surpassing foreign models [1][2]. - There is a lack of self-developed, breakthrough architectural innovations in China, which hampers competitiveness [2]. 2. **Computational Power** - Chinese AI companies have significantly lower GPU computational power compared to international giants like Microsoft, Google, and Meta, often by an order of magnitude [2]. - The ongoing US-China trade war has restricted resource availability, further impacting computational capabilities [1][2]. 3. **Cost and Performance Focus** - Domestic models prioritize inference cost and cost-effectiveness, aligning with local consumer habits, while international models like GPT focus on top-tier performance [1][2]. - The commercial model differences create a substantial gap in model capabilities [2]. 4. **Data Acquisition** - The relatively lenient data laws in China provide an advantage in data acquisition for training models, unlike the stringent regulations in Europe and the US [3]. 5. **Open Source Strategies** - Alibaba adopts a nearly fully open-source strategy, including model weights, code, and training data, to enhance influence and integrate its cloud services [4]. - Other companies like ByteDance and Kuaishou are more selective in their open-source approaches due to their reliance on proprietary technology [4]. 6. **Multimodal Model Developments** - Domestic companies are making strides in multimodal models, focusing on applications in e-commerce and short videos, which cater to local needs [5][6][7]. - Companies like Alibaba, Kuaishou, Tencent, and ByteDance are developing models that integrate text, image, audio, and video generation [7][8]. 7. **MoE Architecture Adoption** - The MoE architecture is becoming standard among major companies, allowing for reduced computational costs and inference times [10]. - Future optimization directions include precise input allocation, differentiated expert system structures, and improved training stability [10][11]. 8. **Economic Viability of Large Models** - Starting mid-2024, pricing for APIs and consumer services is expected to decrease due to the release of previously constrained GPU resources [13]. - The overall cost conversion rate in the large model industry is increasing, despite initial low profit margins [13][14]. 9. **Competitive Differentiation** - Key competitive differences among leading domestic firms will emerge from their unique strategies in technology iteration, data accumulation, and business models [15]. 10. **Future Trends and Innovations** - The focus will shift towards agent systems that integrate user understanding and tool invocation, enhancing overall efficiency [16]. - The MCP concept will gain traction, addressing data input-output connections and reducing integration costs [22]. Additional Important Insights - The acceptance of paid services among domestic users is low, with conversion rates around 3% to 5%, indicating a need for improved user experience to enhance willingness to pay [20][21]. - Successful AI product cases include interactive systems that combine companionship with professional analysis, indicating a potential path for monetization [22]. This summary encapsulates the critical insights from the conference call, providing a comprehensive overview of the current state and future directions of the AI industry in China.

Core Insights - The central theme of the event was "All in AI, All in One, Creation, Infinite New Possibilities," focusing on how AI can reshape the creative process and lower barriers for creators [1][7] - The ultimate goal of the company is to become an "all-around partner" for creators, facilitating a seamless workflow from inspiration to output [1] AI Empowerment - The company has fully integrated AI capabilities in key areas such as "track editing," "audio processing," and "image generation," including the launch of "AI text-to-video" [1][3] - The AI text-to-video feature automates the entire process from script inspiration to storyboard generation and video synthesis, achieving cinematic-level visual quality [1] - AI voice generation 3.0 can produce hyper-realistic voiceovers, indistinguishable from human voices, with future support for multiple dialects and languages [3] - The application of the dreamontage model in AI transition features allows users to upload multiple images or videos for smooth transitions [3] Support for Content Production - The event showcased how creators have utilized AI features in practical applications, highlighting a shift from "point upgrades" to "full-link creative support" [4] - The company has invested over 100 million yuan in cash incentives and increased traffic support to promote AI template creation [6] Community and Collaboration - Creators shared experiences of how AI has become an indispensable collaborative tool in their workflows, enhancing creativity and efficiency [6] - The company aims to transition video creation from being "professionally exclusive" to "universally collaborative," promoting a new brand proposition [7] - Future plans include continuous optimization of features and the introduction of AI technology across the entire creative process, from inspiration to final output [7]