近期，随着人工智能领域的热度持续攀升，市场内外开始弥漫起一种声音：股市是否正站在AI泡沫破裂的悬崖边？这一话题引发了广泛关注和热烈讨论。 尽管对当前的市场状况持谨慎态度，但奥尔特曼对于OpenAI自身的未来却充满了信心。他表示，在不久的将来，OpenAI将在数据中心建设上投入数万亿美 元。这一举措虽然可能会引发一些经济学家的担忧，但奥尔特曼暗示，这并不会影响OpenAI的稳定发展。 OpenAI的首席执行官萨姆·奥尔特曼，在最近接受多家媒体联合采访时，针对这一疑问给出了他的看法。他坦言，目前确实处于投资者对AI技术过度乐观的 阶段。为了说明这一点，奥尔特曼将当前的市场反应与上世纪90年代的互联网泡沫进行了类比。那时，互联网初创企业的估值迅速飙升，但最终在2000年遭 遇了惨痛的崩盘。 "在泡沫中，总会有人损失惨重，也会有人大赚一笔。"奥尔特曼说道，"但从宏观角度来看，这可能对整个经济发展是有利的。当然，这只是我的个人观 点，也许我是错的。" "泡沫的共同特征在于，聪明人往往会对某个核心真相产生过度兴奋。"奥尔特曼解释道，"回顾历史上的泡沫事件，如科技泡沫，背后都有一个不可否认的 事实——科技确实具有划时代的意 ...

Group 1: Chip Industry - Export licensing fees are impacting Nvidia and AMD [3] - The U.S. is embedding trackers in chip exports [3] Group 2: Computing Power - Tesla's Dojo team has been disbanded [3] - Inspur is launching super-node AI servers [3] Group 3: AI Models - OpenAI's GPT-4o is making a comeback [3] - GPT-5 Pro is being developed by OpenAI [3] - Zhiyuan's GLM-4.5 has been released [3] - Kunlun Wanwei's SkyReels-A3 is now available [3] - Zhiyuan has open-sourced GLM-4.5V [3] - Tencent has introduced Large-Vision model [3] - Anthropic is working on a million-context model [3] - Kunlun Wanwei's Skywork UniPic 2.0 has been launched [3] Group 4: AI Applications - xAI has made Grok 4 available for free [3] - Tencent's CubeMe is integrating with mixed yuan [3] - Alibaba is developing embodied intelligence components [3] - Baichuan Intelligence has released Baichuan-M2 [3] - OpenAI's IOI Gold Medal has been awarded [3] - Kunlun Wanwei's Matrix-3D is now available [3] - SenseTime has introduced AI tools for film production [4] - Apple's new Siri is being developed [4] - Pika is working on audio-driven performances [4] - Claude Code has launched Opus planning mode [4] - Kunlun Wanwei's Deep Research Agent v2 is now available [4] - Tencent's Hunyuan-GameCraft is being developed [4] - Microsoft has outlined five modes for AI agents [4] - The OpenCUA framework is being developed by HKU and others [4] Group 5: Technology Developments - Over 100 robots were showcased at the World Robot Conference [4] - Agile intelligent robots are being developed by Lingqiao Intelligent [4] - Figure is working on robots that can fold clothes [4] - Apple's AI suite is being expanded [4] - Zhiyuan Robotics has launched an open-source world model platform [4] Group 6: Industry Insights - Wang Xingxing discusses the development of embodied intelligence [4] - Product Hunt highlights AI product releases [4] - Nvidia and others are exploring physical AI [4] - Scaling Law is being analyzed by Bi Shuchao [4] - The application of large models is discussed by Artificial Analysis [4] - Programming ability assessments are being conducted by foreign developers [4] - DeepMind emphasizes the importance of Genie 3 [4] - Notion is working on AI product standards [4] - Greg Brockman addresses algorithm bottlenecks [4] - Wang Xiaochuan discusses medical large models [4] Group 7: Capital Movements - Meta has acquired WaveForms [4] - Periodic Labs is securing funding for AI materials [4] - OpenAI is investing in brain-machine interfaces [4] - Perplexity has acquired Chrome [4] Group 8: Events - OpenAI is involved in AI chess events [4] - GitHub has merged with CoreAI [4]

据了解，此次大赛将从三个方面为广西发展注入新动能：一是通过"实战攻防赛道"的实测演练，结 合"清朗·AI专项整治"行动，提升广西在用AI应用的安全防护能力。二是推动优秀项目在广西落地孵 化，形成以广西为承载地的技术成果转化体系，带动本地企业技术升级，提升核心技术自主可控水平。 三是打造"广西先行—东盟可复制"的示范案例，例如智慧社区安全解决方案等，通过中国—东盟合作平 台推广，构建应用生态，强化广西在人工智能安全领域的引领地位。（伍永志） 8月15日，记者从相关部门获悉，中国—东盟"护航丝路"人工智能安全大赛已吸引86支区内外队伍 踊跃报名，考虑到高校开学等实际情况，大赛报名时间延长至8月25日，持续向人工智能领域的企业、 高校和专业团队敞开大门。 自AI赋能千行百业超级联赛启动以来，中国—东盟"护航丝路"人工智能安全大赛各项工作稳步推 进。目前，从比赛的五个赛道报名情况来看，实战攻防赛道以42支队伍报名成为热门首选，应用安全赛 道吸引24支队伍，数据安全赛道有9支队伍参赛。此外，在区外报名参赛的15支队伍中，三六零科技集 团有限公司、天融信科技集团股份有限公司、华中科技大学等重要队伍的加入，更为赛事增添看点 ...

Core Viewpoint - Meta has released a new open-source visual model, DINOv3, which demonstrates that self-supervised learning models can outperform weakly supervised learning models across a wide range of tasks [1][3]. Group 1: Model Overview - DINOv3 utilizes an unlabelled approach, expanding the dataset to 1.7 billion images and the model size to 7 billion parameters, effectively supporting applications where data labeling is scarce or costly [1][6]. - The model shows superior performance in scenarios lacking labels or across domains, achieving state-of-the-art (SOTA) results in the three core tasks of computer vision: classification, detection, and segmentation [3][22]. Group 2: Training Methodology - The training process of DINOv3 consists of two main phases, focusing on large-scale self-supervised training to learn high-quality visual representations [8]. - A new method called "Gram anchoring" is introduced to address the degradation of dense feature maps during training, significantly enhancing local feature quality without compromising global features [15][20]. Group 3: Performance Metrics - DINOv3 outperforms its predecessor DINOv2 in various benchmarks, such as achieving 55.9 in segmentation on ADE-20k and 90.4 in image classification on ImageNet ReaL [4]. - The model's training strategy includes RoPE-box jittering, enhancing robustness to variations in resolution, scale, and aspect ratio while maintaining training stability [13][14]. Group 4: Practical Applications - DINOv3 has demonstrated strong generalization capabilities, such as analyzing satellite imagery to detect tree loss and land use changes, providing significant support for global forest restoration and agricultural management [27][28]. - The model has achieved SOTA results in multiple remote sensing tasks, including semantic geospatial tasks and high-resolution semantic tasks [29]. Group 5: Future Implications - The DINO series represents Meta's ongoing exploration of self-supervised methods in the visual domain, marking significant progress in large-scale self-supervised training [30][38]. - DINOv3 is expected to accelerate the development of existing applications and unlock new scenarios across various industries, including healthcare, environmental monitoring, autonomous driving, retail, and manufacturing [39].

⼀、 端到端盛行的当下，轨迹预测这个方向还有研究价值吗？ 最近有同学后台问我们，现在都是搞端到端了，前面的轨迹预测和规划控制还有啥研究的价值吗？端到端真的 上车的并不多，很多依然沿用分层方案，其中轨迹预测作为后半段的核心算法，依然是许多公司和机构研究的 热点。包括联合轨迹预测和目标轨迹预测。相关的会议和期刊依然有较大量的工作产出。 自动驾驶之心针对目前比较火的基于扩散模型的多智能体轨迹预测方法研究展开了首个1v6小班课！本课题聚 焦于"基于扩散模型的多智能体轨迹预测方法"。多智能体轨迹预测旨在根据多个交互主体的历史轨迹，预测其 未来运动轨迹，这在自动驾驶、智能监控和机器人导航等场景中至关重要。然而，由于人的行为具有不确定性 和多模态性，预测任务十分困难。传统方法通常依赖循环神经网络、卷积网络或图神经网络建模社会交互，而 生成模型（如GAN和CVAE）虽然可以模拟多模态分布，但效率不高。 扩散模型是一类通过逐步去噪实现复杂分布生成的新型模型，近年来在图像生成等领域取得了重大突破。研究 者发现将扩散模型应用于轨迹预测可以显著提升多模态建模能力。例如，LeapfrogDiffusionModel（LED）采 用可训 ...

This company is struggling to generate a profit.Shares of C3.ai (AI) fell 19% this week, according to data from S&P Global Market Intelligence. The artificial intelligence (AI) company, which builds enterprise applications, released dismal preliminary financial results for its latest quarter, while the company's CEO announced that he would be departing the company. C3.ai has never generated a profit, and its stock is down 90% from all-time highs set from its initial public offering (IPO).Here's why the stoc ...

况阳/文 人工智能时代来了！ 开创性工作的科学家们。人工智能，这个曾被人嘲笑、被人视为边缘的研究方向，终于走到了时代的正 中央。 至此，还有谁会质疑人工智能时代已来的事实？ 如今的人工智能，早已不再是工程师手中的技术玩具，也不再是只会写诗陪聊的"话痨"，而是实实在在 的革命性生产力利器。对此，华为创始人任正非先生看得尤为透彻，他断言："人工智能的潜力巨大， 可能成为人类社会最后一次颠覆性的技术革命。" 而这场革命，给职场人带来的最直接、最迫切的冲击就是——工作的范式正在被彻底改写。 当2016年有人这么说时，一定不会有多少人相信，以为那不过是技术人的自我贴金，是在"刷存在感"。 那一年的3月16 日，人工智能领域发生了一件大事——谷歌的AlphaGo战胜了人类围棋冠军李世石。五 局对战，人工智能以4比1的压倒性优势胜出。这是继1997年IBM的"深蓝"机器人战胜国际象棋大师卡斯 帕罗夫后，人工智能领域取得的又一个里程碑式胜利。战胜国际象棋大师本已不易，而战胜围棋大师就 更是难上加难，要知道一直以来，围棋都被视为人类最后的智力自留地。从计算量上看，围棋的难度是 象棋的1亿倍。但即便如此，不少人依然选择漠视，仍旧 ...

The company's business has been growing at a fast pace, but questions about profitability still linger.For investors who don't want to simply load up on Nvidia and other already established artificial intelligence (AI) companies, it can be challenging to find the next big AI stock to buy. There are a lot of companies that claim they have AI-powered products and services -- and sprinkle the term AI into all of their press releases and reports -- but simply being involved with AI doesn't mean that a stock is ...

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 ...