Group 1 - The AI sector experienced a pullback on June 10, with a cooling of the recent tech revaluation narrative, but AI capital expenditures are expected to remain high, supported by policy initiatives [1] - Major cloud providers and tech companies showed a year-on-year capital expenditure growth at historical highs, unaffected by tariffs and macroeconomic factors, indicating a potential independent trend for AI [3] - The commercial prospects for AI agents and embodied intelligence, particularly humanoid robots, are promising, with significant policy support and a thriving ecosystem led by major players like Alibaba and Tencent [8] Group 2 - The "DeepSeek moment" has driven the tech revaluation narrative in China, although it has recently cooled, leading to an expanded valuation gap between Chinese and U.S. tech giants [8] - The semiconductor equipment ETF (159516), chip ETF (512760), and the entrepreneurial AI ETF (159388) are suggested as potential investment vehicles for interested investors [8]

It's a nice way to to think about it from idea to IPO. But you know like that's the history of Silicon Valley, right. That's what every founders sets out to do.Among those 11, what are you most proud of. What was the sort of steepest arc, would you say. It's great to be here.You know, we've at notable really built our business around focusing on the founder. And I think the primary lesson we've learned from the successes we've had is that if we serve founders really well, if we provide them with a unique ex ...

Hi, I'm Robert. I'm the co-founder and CTO at Wordware. And at Wordware, I've personally helped hundreds of teams build reliable AI agents.I'm here to share a few of the insights that we got, especially when it comes to tools. Um, really agentic MCPs, giving your tools time to think. Before I worked on uh LLMs and agents, I used to work on self-driving cars, and really, you know, building high reliable systems is in my blood.So, uh, yeah, here we go. The promise of agents are automated systems that can take ...

All right. Hello everyone. Uh, thanks for being here and joining us on this nice Wednesday afternoon.Uh, my name is Matasanis and this is my colleague. Hey folks, I'm Sorup Sherhhati. And today we're going to present how we built AI developer tools at Uber uh, using Langraph.So to start off, a little bit of context. Um Uber is a massive company serving 33 million trips a day across 15,000 cities. And this is enabled enabled by a massive code base with hundreds of millions of lines of code.And it is our job ...

With the increased use of NHIs and AI agents, especially with machine identities, there is a huge opportunity for Okta. This goes the same for the Total addressable market (TAM). As of now, Okta (NASDAQ: NASDAQ: OKTA ) is amongAnalyst’s Disclosure:I/we have a beneficial long position in the shares of OKTA either through stock ownership, options, or other derivatives. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have ...

Summary of Conference Call Records Industry Overview - The conference call discusses the advancements in enterprise-level AI applications, particularly in the ERP (Enterprise Resource Planning) sector, highlighting the integration of AI technologies to enhance various modules such as finance, supply chain, CRM (Customer Relationship Management), and EPM (Enterprise Performance Management) [1][3][4]. Key Points and Arguments 1. **AI Enhancements in ERP Systems**: AI significantly improves ERP functionalities, with domestic systems leveraging deep learning algorithms to enhance operational efficiency and value creation [1][3]. 2. **Rapid Iteration of AI Products**: ERP systems are rapidly iterating AI products based on models like GPT-4 and domestic DeepThink, improving intelligent reception capabilities [1][4]. 3. **Challenges for Domestic ERP Vendors**: Domestic ERP vendors face challenges such as insufficient feature improvements and a market that demands practical solutions rather than mere technological hype [1][5]. 4. **Huawei's AI Integration**: Huawei integrates its DeepSeek model into its self-developed ERP system, enhancing management capabilities and planning to market this solution [1][8]. 5. **Oracle's Competitive Edge**: Oracle utilizes its Fusion ERP middleware, combining deep learning and GPT algorithms to provide decision support and maintain competitive advantages [1][9][10]. 6. **AI's Impact on Efficiency**: Implementing AI can significantly enhance efficiency across various business functions, including HR, marketing, sales, supply chain, and finance [1][11]. 7. **Differences in Domestic and International ERP Markets**: The international ERP market is more capitalized and performance-driven compared to the domestic market, which has unique challenges and growth rates [1][12]. 8. **Vertical Software Companies**: Vertical software companies in China, like Guodian NARI, perform well due to their specialized offerings and pricing power [1][13]. 9. **Oracle's AI for Fusion**: Oracle's AI for Fusion helps businesses unlock AI value through predictive modeling, anomaly detection, and actionable insights [1][14][15]. 10. **Dynamic Reporting Capabilities**: Oracle's management reports are dynamic, reflecting real-time data updates and supporting multiple workflows [1][16]. 11. **Unique Advantages of Oracle**: Oracle's products are based on Java, allowing for easier integration and faster deployment compared to competitors like SAP [1][24]. 12. **Client Base in China**: Oracle has a diverse client base in China, including major companies and government departments, utilizing localized ERP systems [1][29]. 13. **Challenges for Chinese Enterprises**: Chinese enterprises face challenges in data accumulation and require robust digital transformation to leverage AI effectively [1][32]. Additional Important Content - **AI Commercialization**: The call discusses how AI commercialization can be achieved by embedding AI technologies into enterprise models, with examples from Huawei and Oracle [1][6]. - **SAP's Market Exit**: SAP is exiting the Chinese market due to its product limitations and lack of localization, which does not meet the complex needs of Chinese enterprises [1][23]. - **Oracle's Service Quality Assurance**: Oracle has implemented a compensation mechanism for service disruptions, showcasing its confidence in product quality [1][31]. This summary encapsulates the key insights and developments discussed in the conference call, focusing on the impact of AI on the ERP industry and the competitive landscape among major players like Oracle and Huawei.

每周日至每周四推送明日股市重大公告！内容包含"停复牌、增减持、投资中标、收购、业绩、解禁、 高送转"等一系列个股利好利空公告，其中重要公告均以红色标注，帮助投资者提前寻找到投资热点， 防范各类黑天鹅事件，并且有充足的时间进行分辨和寻找合适的上市公司。 ①创新药+机器人+AI智能体+脑机接口！这家公司参与设立新产品战略相关基金主要投资于创新药等领 域；②固态电池+可控核聚变+算力+机器人+体育产业+国企改革！这家公司固体氧化物电池研发项目在研 发攻关过程中；③固态电池+机器人！这家公司与小米下属公司战略合作研发机器人电子皮肤。 前言 ...

So robot body process automation is literally if human had to do something you basically open some browser or whatever take some data put into some other system click some button and all that stuff. So it records that human clicks on that desktop and tries to keep repeating it. So you kind of like get that automated and the hard part that they had is you can't do robotic process for unstructured data because it's not fixed they change it.So anything will be very very brutal. The bet that we are taking is th ...

今天分享的是：传媒：AI Agent生态建设提速，B、C两端价值明确 报告共计：82页 《传媒：AI Agent生态建设提速，B、C两端价值明确》指出，AI Agent作为生成式AI商业化落地的关键形态，正从工具向智能工作体演进，其核心 在于通过模型、工具与多智能体通信协议（A2A）构建任务自动化处理能力。国际巨头如OpenAI、Google、微软等已在Agent开发框架、多模态交 互及企业级应用领域形成突破，例如OpenAI的Operator智能体可模拟人类操作浏览器完成复杂任务，Google的A2A协议实现智能体间协作，微软的 Microsoft 365 Copilot则深度整合办公场景。 国内互联网大厂加速布局：阿里巴巴推出Qwen-Agent开源框架，支持函数调用与RAG技术，其"扣子空间"实现多智能体协作完成行业报告分析；腾 讯"元器"基于混元大模型构建一站式AI Agent开发平台，覆盖微信生态全链路；百度"文心智能体平台"提供从智能体创建到插件集成的全流程工 具，支持个性化智能体快速部署；字节跳动"Coze"推出零代码AI Agent开发工具，支持接入Discord、微信等多平台，实现内容生成与 ...

作者丨樱木 编辑丨九黎 2025年5月，红杉资本AI峰会在旧金山落下帷幕。这场汇聚150位全球顶尖AI公司创始人的大会达成重要共识：下一轮AI竞争的核心不再是工具本 身，而是为用户创造的实际收益。在此背景下，Agent的重要性被前所未有的推至所有人的视野前沿。 硅谷大厂开启了第一波加速，微软CEO纳德拉在主题演讲中宣布："我们已经进入了AI Agent时代，正在见证AI系统如何以全新方式帮助我们解决 问题。"Open AI CEO山姆·奥特曼宣布，推出面向开发者的新Codex Agent，称"这可能是编程史上最大的变革。" 而将目光聚焦到国内，大厂纷纷亲自下场，当没人怀疑AI Agent确定性时，实用性的困境却在继续。用户喜欢用"AI实习生"来诠释当下AI Agent的 能力。 从实际情况来看，所谓"AI实习生"直接揭示的是当下AI Agent无法在泛化场景下，满足企业和个人的执行落地要求。特别是当企业进入到数字化 转型的深水区，具体的场景和数据开始细化，传统AI难以打通数据孤岛，员工困囿于重复工作等问题就显得异常突出，关于AI agent的升级似乎 迫在眉睫。 如何解决这一困境，一直聚焦于大模型商业化的智谱 ...