对于当前 AI 初创企业的融资现状，奥尔特曼直言"疯狂"："一些 AI 初创企业仅仅只有'三个人和一个想法'，却能获得极高估值融资，这种现象并不理性， 我认为总有人会在这上面栽跟头。" 过去一年内，全球已经有多个 AI 初创企业筹得巨额资金，其中也包括由 OpenAI 联合创始人伊利亚・苏茨克维（Ilya Sutskever）领导的 Safe Superintelligence，以及由前 OpenAI 首席技术官米拉・穆拉蒂（Mira Murati）创办的 Thinking Machines。 IT之家 8 月 15 日消息，随着最近两年 AI 热潮的兴起，我们能看到有越来越多的人开始讨论股市是否正处于 AI 泡沫破裂的边缘。 对于是否正处于投资者对 AI 过度兴奋的阶段？OpenAI 首席执行官萨姆・奥尔特曼（Sam Altman）昨日在接受《The Verge》等媒体的联合采访时表示，"我 的看法是，是的"。 在采访中，他将市场对 AI 的反应与上世纪 90 年代的互联网泡沫进行比较。当时互联网初创企业的估值在短时间内大幅飙升，并于 2000 年出现崩盘。 "泡沫的共性是，聪明人会对一个核心真相过度兴奋。 ...

The Q2 earnings season remains robust and continues to improve, with an above-average share of companies topping estimates and outlooks strengthening for both the current and upcoming periods. Among the 457 S&P 500 companies that have reported so far, total earnings are up 11.6% year over year on 5.8% higher revenues, with 80.5% beating EPS forecasts and 78.8% surpassing revenue expectations.The proportion of the 457 index members beating EPS and revenue estimates is tracking notably above the historical av ...

Core Insights - Users who paid for GPT-5 seem to be disappointed with the lack of significant improvements compared to previous versions [2] - Free users, however, may have a different experience, as ChatGPT has over 700 million free users and ranks as the 5th most visited website globally, surpassing platforms like X and Reddit [3] - SemiAnalysis suggests that the Router mechanism in GPT-5 allows OpenAI to extract commercial value from a large base of free users [4] Group 1: Router Mechanism - The Router is a core feature of GPT-5, enabling it to function as a unified system that includes a general model, a deep reasoning model, and a real-time Router [6] - This Router can direct user requests to the appropriate model based on the complexity and intent of the query, thus optimizing both cost and performance [7] - The introduction of the Router has led to a sevenfold increase in free users accessing the "thinking" model on the first day of its launch, with paid users increasing by nearly 3.5 times [7] Group 2: Monetization Strategies - OpenAI is beginning to seriously consider monetizing free users, with a focus on controlling user experience to open up more revenue streams [12] - Sam Altman's perspective on advertising has shifted, indicating a willingness to explore monetization through potential revenue-sharing models [14][16] - The Router's ability to understand user intent could facilitate a transition to a consumer-focused super-app, allowing for transaction-based revenue generation [16][30] Group 3: Agentic Purchasing Model - The concept of Agentic purchasing contrasts with traditional search queries, as LLMs can dynamically allocate resources based on the commercial value of queries [18][22] - The Router allows for differentiation between low-value and high-value queries, enabling more efficient resource allocation and potentially higher-quality responses [22][25] - This model could evolve into a super-app that facilitates everyday consumer decisions, with revenue generated through transaction fees rather than subscription costs [26][30] Group 4: Competitive Landscape - OpenAI's Router is poised to challenge Google's ad-centric business model, as it leverages a large user base to create a new monetization pathway [37][41] - Smaller companies are already benefiting from AI recommendations, with significant traffic driven by ChatGPT, indicating a shift in consumer behavior away from traditional search engines [42] - The emergence of AI-driven purchasing could disrupt established players like Google and Amazon, as OpenAI positions itself as a formidable competitor in the consumer space [47][48]

智通财经APP获悉，8月15日，网龙（00777）及其子公司创奇思（Cherrypicks）联同中科闻歌，今日共同举办"引领未 来AI移动智能：网龙旗下创奇思与中科闻歌战略联盟成立仪式"，致力于推动人工智能技术于企业及教育领域的创新 应用。此次合作不仅标志着中国AI核心技术首次由香港企业牵头走向国际，更为香港AI生态注入强大动力，促进香港 成为大湾区及国际AI创科枢纽，推动中国AI技术出海，引领香港AI生态再迈新台阶。 网龙旗下创奇思与中科闻歌将在中国内地以外地区展开独家合作，共同推广人工智能服务。网龙旗下创奇思将成为中 科闻歌于境外市场的唯一独家出海平台与商业化伙伴。中科闻歌投资创奇思，并将向其投入AI技术资源，支持双方在 公共服务、金融、医疗及商业等领域共同研发并落地面向境外市场的产品与解决方案。中科闻歌董事长王磊博士将加 入创奇思董事会，协调合作发展方向与技术路线，推动项目高效落地。 网龙、中科闻歌及网龙旗下创奇思管理团队共同庆祝网龙旗下创奇思与中科闻歌战略联盟正式成立 网龙副董事长梁念坚博士指出，这次三方合作，是中国AI技术"出海"和香港创科实力融合的典范。网龙旗下创奇思作 为连接内地与国际市场的桥梁 ...

Core Viewpoint - The article discusses the release and open-sourcing of the formal theorem proving models StepFun-Prover-Preview-7B and StepFun-Prover-Preview-32B by the company, highlighting their advanced capabilities in formal proof generation and refinement through interactive learning [1][16]. Technical Highlights - StepFun-Prover employs a reinforcement learning training process based on environmental feedback, allowing the model to iteratively correct and improve formal proofs through real-time interaction [2]. - The two-stage supervised fine-tuning (SFT) strategy is utilized, where the first stage equips the model with basic tool usage capabilities [4]. - Tool-integrated reinforcement learning (RL) is implemented, where the model learns to generate outputs by utilizing Lean 4 data for code completion and understanding mathematical problem-solving [5]. - The iterative optimization method "RL-SFT-RL" enables the model to tackle increasingly difficult reasoning tasks, enhancing its performance over time [8]. Performance Metrics - The StepFun-Prover-Preview-32B achieved a pass@1 accuracy rate of 70.0% on the miniF2F-test benchmark, surpassing all known models by over 4% [9]. - The StepFun-Prover-Preview-7B also outperformed other models, including DeepSeek-Prover-V2-671B and Kimina-Prover-72B, with a pass@1 accuracy of 66.0% [10]. Case Studies - Case 1 demonstrates the model's ability to actively remove redundant steps in formal proofs, showcasing its natural language processing and feedback analysis capabilities [11]. - Case 2 illustrates how the model adjusts the structure of formal proofs based on timeout feedback, enhancing its adaptability [13]. - Case 3 highlights the model's effectiveness in correcting errors based on environmental feedback, further improving its reasoning robustness [12]. Future Directions - The StepFun-Prover Preview represents a significant milestone for the company in the field of formal proofs, with ongoing exploration in formal reasoning models anticipated [16].

闻乐 发自 凹非寺 量子位 | 公众号 QbitAI 以上，均是腾讯混元3D世界生成模型HunyuanWorld 1.0在 消费级显卡 上跑出来的—— 发布即 开源 ，还可兼容传统CG管线，低门槛操作但高质量生成。 只需要一句话或一张图片，就能生成360度全景3D世界。 还支持沉浸式漫游。 与最近爆火的Genie3只能生成视频不同，该模型还可以导出能进行二次编辑的3D mesh。 下面咱们边看效果边说技术。 分层实现3D生成，量化降低显存开销 HunyuanWorld 1.0技术框架的核心是 以全景图为桥梁，分层实现3D生成 ，通过借助2D生成技术的多样性做出丰富场景，再基于全景图实 现3D生成的连贯性。 场景生成的关键流程可以概括为三步： 首先根据文字或图片输入，生成无边界断裂、无几何变形的360°全景图。 分层场景生成 接着 将全景图拆分为天空、背景、前景物体 等可独立操作的语义图层。 最后为各图层标注合理深度，再按图层特性分别转化为3D结构，同时支持导出标准3D模型。 在此基础上，框架还做了两项实用优化：一是通过 点云缓存与视频扩散技术 ，实现长距离场景的无缝漫游； 二是针对3D模型的在线/离线双模式压 ...

Core Viewpoint - The ongoing scrutiny of Benchmark's investment in Manus by the U.S. Treasury Department highlights the complexities of the Reverse CFIUS regulations and their implications for U.S.-China investment dynamics, particularly in the AI sector [2][24][28]. Group 1: Manus and Benchmark's Situation - The U.S. Treasury's investigation into Benchmark's investment in Manus stems from the Reverse CFIUS ban, which restricts U.S. capital from investing in Chinese AI, semiconductor, and quantum information technology sectors [2][4]. - Manus has taken significant steps to mitigate scrutiny, including relocating its headquarters to Singapore and reducing its domestic workforce, signaling a shift towards embracing overseas markets [7][8][22]. - The potential forced divestment of Benchmark could lead to a chain reaction, prompting other investors to reconsider their positions in Manus, thereby impacting its funding and operational capabilities [15][24][28]. Group 2: Implications for the AI Industry - Manus's case may set a precedent for how the U.S. Treasury interprets and enforces Reverse CFIUS regulations, leading to stricter scrutiny of other Chinese AI startups seeking U.S. investment [24][26]. - The politicalization of U.S. capital could create a more challenging financing environment for Chinese AI companies, pushing them to seek alternative funding sources outside the U.S. [26][28]. - The importance of compliance in offshore structures is becoming increasingly critical for Chinese AI startups, as they must navigate complex regulatory landscapes to avoid scrutiny [26][28].

【导读】无需人工标注，吞下17亿张图片，Meta用自监督学习炼出「视觉全能王」！NASA已将它送上火星，医疗、卫星、自动驾驶领域集体沸腾。 | Task | DINO | DINOv2 | DINOv3 | SigLIP 2 | PE | | --- | --- | --- | --- | --- | --- | | Benchmark | ViT-B/8 | ViT-g/14 | ViT-7B/16 | VIT-g-OPT/16 | ViT-G/14 | | | 0.09B | 1.1B | 7B | 1.8B | 1.98 | | Segmentation ADE-20k | 31.8 | 49.5 | 55.9 | 42.7 | 38.9 | | Depth estimation NYU I | 0.537 | 0.372 | 0.309 | 0.494 | 0.436 | | Video tracking DAVIS | 68.7 | 76.6 | 83.3 | 62.9 | 49.8 | | Instance retrieval Met | 17.1 | 44.6 | 55.4 | 13.9 | 1 ...

Core Viewpoint - Meta has made headlines by offering a record-breaking compensation package of $250 million to 24-year-old AI researcher Matt Deitke, highlighting the intense competition in the AI industry for top talent [2][3][15]. Group 1: Meta's Recruitment Strategy - Meta's CEO Mark Zuckerberg personally contacted Deitke to recruit him for a new "superintelligence" research project aimed at developing AI systems that could potentially surpass human intelligence [2]. - Initially, Meta offered Deitke a four-year compensation package worth approximately $125 million, which was later increased to $250 million after he declined the first offer [2][3]. - Deitke's acceptance of the offer reflects the escalating salaries for AI talent, with his compensation surpassing historical figures in science and technology [15][16]. Group 2: Deitke's Background and Achievements - Deitke previously dropped out of a PhD program at the University of Washington and co-founded a startup called Vercept, which focuses on creating AI agents capable of independent decision-making [11]. - He was a key member in developing Molmo, a multimodal chatbot that integrates text, images, and voice for complex understanding and reasoning tasks [8][11]. - The success of Molmo is attributed to its innovative training dataset, PixMo, which enhances the chatbot's capabilities in visual language processing [9][11]. Group 3: Industry Reactions and Implications - The astronomical salary has raised eyebrows among industry insiders, with some questioning the justification for such a high compensation for a relatively young and less experienced researcher [6][14]. - Comparisons have been made to historical figures in science, illustrating how Deitke's salary far exceeds those of renowned scientists from previous eras [15]. - The situation indicates a shift in the tech industry where AI researchers are now being compensated similarly to top athletes, marking a new era in talent acquisition and valuation [16][17]. Group 4: Talent Competition and Future Outlook - The fierce competition for AI talent has led to significant changes in recruitment strategies across companies like OpenAI and Google, with firms adjusting their compensation structures to retain employees [18]. - Meta's aggressive hiring strategy is seen as a bet on the future potential of young AI researchers, positioning them as key players in shaping the next technological landscape [24][25]. - The trend suggests that even lesser-known researchers can achieve significant financial success in the current AI talent market, reflecting a broader shift in the industry's dynamics [19][20].

Core Viewpoint - OpenAI's release of GPT-5 has generated significant attention and mixed reactions, with high expectations from the public but also notable criticisms regarding performance and user experience [2][3][4]. Group 1: User Feedback and Criticism - Some users reported dissatisfaction with GPT-5, citing slower response times and inaccuracies in answers, leading to frustration and even subscription cancellations [3][4]. - Users expressed disappointment over the removal of previous models without notice, feeling that OpenAI disregarded user feedback and preferences [3][4]. - Despite the criticisms from individual consumers, the enterprise market has shown a more favorable reception towards GPT-5, with several tech startups adopting it as their default model due to its improved deployment efficiency and cost-effectiveness [4][5]. Group 2: Enterprise Adoption and Testing - Notable companies like Box are conducting in-depth testing of GPT-5, focusing on its capabilities in processing complex documents, with positive feedback on its reasoning abilities [5]. - The rapid adoption of GPT-5 by tech startups highlights its advantages over previous models, particularly in handling complex tasks and reducing overall usage costs [4][5]. Group 3: Future Implications and AI Development - Sam Altman discussed the potential of GPT-5 to revolutionize various tasks, emphasizing its ability to assist in software development, research, and efficiency improvements [10][11]. - The conversation around GPT-5 also touched on the broader implications of AI in society, including the importance of adaptability and continuous learning in a rapidly changing technological landscape [16][19]. - Altman highlighted the significance of mastering AI tools as a critical skill for the future workforce, particularly for young entrepreneurs [15][16].