马斯克一手开源动作，引发了大伙儿的高度关注—— xAI现在正式开源Grok 2.5，Grok 3将在半年后开源。 其实早在本月初的时候，马斯克就公开表示过： 是时候开源Grok了，将会在下周。 目前，Grok已经可以在HuggingFace中下载（链接附文末）： | xAI官方建议用SGLang来运行Grok 2，具体步骤如下。 | | --- | 第一步，下载权重文件。 你可以把 /local/grok-2 换成任何你喜欢的文件夹名字： hf download xai-org/grok-2 —local-dir /local/grok-2 官方表示，这个下载过程中可能会遇到一些错误，如果出错了，可以多试几次直到下载成功。 下载成功后，文件夹里应该有42个文件，大小约为500GB。 第二步，启动服务器。 虽然开源的时间已经超过了他说的节点，但也正如网友所说： 迟到总比没有的好。 42个文件，500个G xAI官方建议安装最新版的SGLang推理引擎（版本号 >= v0.5.1，地址为：https://github.com/sgl-project/sglang/）。 然后用下面的命令来启动推理服务器： pyth ...

每经AI快讯，北京时间8月24日，特斯拉CEO马斯克在X上官宣，xAI去年最好的模型Grok-2.5（实际上 是Grok-2）正式开源，同时，Grok-3也将在大概6个月内开源。马斯克同时发表观点表示，xAI很快就会 超越除谷歌外的任何公司，然后也将超越谷歌，"但中国公司将是最强劲的竞争对手，因为他们的电力 比美国多得多，而且在硬件建设方面实力超强。" ...

金磊 发自 凹非寺 量子位 | 公众号 QbitAI 就在刚刚，马斯克一手开源动作，引发了大伙儿的高度关注—— xAI现在正式开源Grok 2.5，Grok 3将在半年后开源。 其实早在本月初的时候，马斯克就公开表示过： 是时候开源Grok了，将会在下周。 虽然开源的时间已经超过了他说的节点，但也正如网友所说： 迟到总比没有的好。 42个文件，500个G 目前，Grok已经可以在HuggingFace中下载（链接附文末）： | xAI官方建议用SGLang来运行Grok 2，具体步骤如下。 | | --- | | 第一步，下载权重文件。 | | 你可以把 /local/grok-2 换成任何你喜欢的文件夹名字： | | hfdownload xai-org/grok-2—local-dir /local/grok-2 | | 官方表示，这个下载过程中可能会遇到一些错误，如果出错了，可以多试几次直到下载成功。 | | 下载成功后，文件夹里应该有42个文件，大小约为500GB。 | | 第二步，启动服务器。 | | xAI官方建议安装最新版的SGLang推理引擎（版本号 >= v0.5.1，地址为：https:/ ...

Core Viewpoint - Mistral AI, founded by three young graduates, is raising $1 billion in a new funding round, reaching a valuation of $10 billion, reflecting a nearly 50-fold increase in just two years [4][8]. Group 1: Company Overview - Mistral AI was established by three 90s graduates who previously worked at top AI companies and returned to France to seize the AI opportunity [8]. - The company launched its first open-source model, Mistral 7B, which outperformed competitors in several benchmarks, quickly gaining attention in the developer community [8][9]. - Mistral aims to lead the generative AI wave through open-source initiatives, contrasting with closed models from competitors like OpenAI [8][9]. Group 2: Funding and Valuation - Mistral AI completed a record seed round of $113 million shortly after its founding, achieving a valuation of over $260 million [12]. - By the end of 2023, Mistral raised $415 million in Series A funding, led by a16z, increasing its valuation to $2 billion [13]. - The company’s valuation skyrocketed to $6 billion after a $640 million Series B round, with major investors including Microsoft and Nvidia [14]. - Currently, Mistral is negotiating a $1 billion funding round, which could elevate its valuation to approximately $10 billion [14]. Group 3: Competitive Landscape - The AI landscape is becoming increasingly competitive, with the emergence of DeepSeek as a significant player, prompting Mistral to accelerate its product development and commercialization efforts [9]. - Mistral has launched several products, including the chatbot Le Chat, which achieved high download rates in France but struggled internationally [9]. - The company is actively pursuing partnerships with industry giants like Nvidia to enhance its market position [9]. Group 4: Young Entrepreneurs in AI - The AI sector is witnessing a surge of young entrepreneurs, with several companies founded by 90s graduates achieving significant funding and rapid growth [16][17]. - Companies like Perplexity and Genesis AI have also seen remarkable valuations, highlighting the trend of young innovators in the AI space [16][17]. - This new generation of entrepreneurs is characterized by their global perspective and technical expertise, positioning them well to capitalize on AI opportunities [18].

Core Viewpoint - Meta is shifting its AI model release strategy to better promote the development of "personal superintelligence," emphasizing the need for careful management of associated risks and selective open-sourcing of content [3][5][11]. Group 1: Shift in Open-Source Strategy - Mark Zuckerberg's recent statements indicate a significant change in Meta's approach to open-source AI, moving from being a "radical open-source advocate" to a more cautious stance on which models to open-source [6][8]. - The company previously viewed its Llama open-source model series as a key competitive advantage against rivals like OpenAI and Google DeepMind, but this perspective is evolving [5][9]. - Meta is unlikely to open-source its most advanced models in the future, which could lead to increased expectations for companies that remain committed to open-source AI, particularly in China [10][11]. Group 2: Investment and Development Focus - Meta has committed $14.3 billion to invest in Scale AI and restructure its AI department into "Meta Superintelligence Labs," indicating a strong focus on developing closed-source models [11][12]. - The company is reallocating resources from testing the latest Llama model to concentrate on developing a closed-source model, reflecting a strategic pivot in its AI commercialization approach [12][14]. - Meta's primary revenue source remains internet advertising, allowing it to approach AI development differently than competitors reliant on selling access to AI models [11]. Group 3: Future of Personal Superintelligence - Zuckerberg envisions "personal superintelligence" as a means for individuals to achieve their personal goals through AI, with plans to integrate this concept into products like augmented reality glasses and virtual reality headsets [14]. - The company aims to create personal devices that can understand users' contexts, positioning these devices as the primary computing tools for individuals [14].

Core Insights - China's open-source AI ecosystem is rapidly evolving, showcasing technological confidence and creating a path for global collaboration, contrasting with the closed-source approach prevalent in the U.S. [1][6][8] Group 1: Open-Source Development in China - DeepSeek and other foundational models like Alibaba's Qwen are driving the advancement of China's open-source capabilities, leading to the emergence of smaller, more powerful vertical models from various SMEs [1][4] - The launch of models like Skywork-OR1 by Kunlun Wanwei demonstrates that even companies with limited funding can achieve state-of-the-art (SOTA) performance by leveraging existing open-source models [4][5] - The rapid iteration of large models in China, such as Alibaba's Qwen2.5-VL and the multi-modal models from Jiepu, indicates a thriving open-source ecosystem [5][6] Group 2: Comparison with U.S. AI Strategy - The U.S. AI industry remains predominantly closed-source, driven by major tech companies and venture capitalists seeking high returns, which fosters a monopolistic environment [6][8] - OpenAI's shift to a closed-source model, particularly after its partnership with Microsoft, highlights the commercial motivations behind this strategy [7][8] - In contrast, China's top-down approach emphasizes open-source development as a means to enhance technological equity and industry collaboration [8][9] Group 3: Economic and Social Implications - The Chinese government has actively supported open-source initiatives, recognizing their potential to lower technological barriers and promote economic integration [8][9] - Investments in open-source projects, such as the Z Fund's commitment to support AI open-source communities, reflect a broader strategy to foster innovation [9][10] - The open-source movement in China is not only about providing free products but also about enabling developers to build upon existing technologies, thus accelerating progress [5][10] Group 4: Practical Applications and Success Stories - Open-source models are being successfully implemented in various industrial applications, such as predictive maintenance in manufacturing and environmental conservation efforts [13][14] - Companies like Baosteel and Zhongmei Kegong are utilizing open-source models to enhance operational efficiency and reduce costs [13][14] - The collaborative nature of open-source development allows for broader participation in AI projects, benefiting both commercial and non-profit sectors [14][15] Group 5: Future Outlook - China's open-source AI landscape is transitioning from a phase of "technological following" to "ecosystem leadership," reshaping the global AI landscape [18][20] - The focus is shifting from mere parameter competition to the deep integration of AI technology with the real economy, indicating a strategic evolution in the industry [18][20]

3 万字全文翻译，被披露的不只是内斗。 文丨贺乾明 翻译、校对丨GPT-4o、Claude-3.5-Sonnet、贺乾明 编辑丨 黄俊杰 "创业公司的内部全都是车祸现场。只是有的你能在媒体上看到，有的看不到。" 山姆·阿尔特曼（Sam Altman）的导师，硅谷孵化器 YC 创始人保罗·格雷厄姆 曾这么总结他看过的千百家创业公司。 得益于阿尔特曼和特斯拉 CEO 埃隆·马斯克的争斗和诉讼，现在我们也能看到 OpenAI 早年的真实样子。双方各自公布了数批共 75 封内部邮件以及短信记 录，时间跨度从 2015 年 OpenAI 筹备到 2019 年组建营利实体，展示了一群硅谷名流和天才 AI 研究者如何因为理想聚在一起，又如何随着 OpenAI 的发展争 权夺利。 这些长达 3 万多字的内部记录也像是一堂 OpenAI 出品的创业课，涉及这家全球最大的 AI 创业公司早期如何讲故事、组建精英阵容，到薪酬设计、股权分配 的方方面面；从低价与 Google 争夺人才到与微软谈判合作，甚至还包括曾考虑过的加密货币融资方案。而且，我们还能看到首席科学家伊利亚·苏茨克维 (Ilya Sutskever) 如何写双周报， ...