4. 法巴银行：欧元区需依靠更多国防和基建支出来缓解老龄化压力 1. 高盛策略师：上调亚洲股票目标，调高港股评级 高盛集团策略师上调了对亚洲股市的预期，理由是宏观经济环境更加有利，关税的确定性增加。以 Timothy Moe为首的策略师在周五的一份报告中表示，MSCI亚太（除日本外）指数的12个月目标指数上 调了3%，至700点，这意味着在此期间以美元计算的回报率为9%。该团队还将港股评级上调至"持 股"（market weight），并称其将在美联储开启宽松周期、美元走弱的背景下成为主要受益者之一。他 们补充称，菲律宾等也是对这一趋势最为敏感、受益最大的市场之一。策略师们表示："关税征收和宽 松的货币政策可能是第三季度对亚洲股市的重要宏观影响。"他们指出，即便最终实施的关税税率略高 于当前的基线预期，"其对基本面增长的冲击可能不会像市场在第二季度初所担忧的那样严重。" 2. 美银：全球经济不确定性中，布油价格保持坚挺 美国银行大宗商品策略师Francisco Blanch表示，尽管今年全球经济增长和地缘政治方面存在不确定性， 但布伦特原油价格仍表现出较强韧性，今年1月以来平均价格维持在每桶70.75美元。这 ...

作者：瀚海 2025年7月10日，孚知流（Fuzflo）正式发布面向"业务专家"的Agent生产与操作系统Leapility，并宣布完成千万级人民币天使轮融资，投资机构为棋兆资 本。Leapility以"驱动能力跃迁的智能引擎"为定位，通过深度挖掘"冰山之下"的隐性专家知识，助力超级个体与企业用户实现专家级Agent的规模化设计与落 地应用。 孚知流成立于2023年，是一家致力于让知识流动的AI创新企业，核心团队成员来自商汤、阿里巴巴等知名科技公司，创始人白双曾获评胡润U30、36Kr 2024影响力女性等荣誉。公司已累计获得数千万元风险投资，并入选亚马逊云科技、微软等顶尖孵化器。 Leapility 自然语言叙事模式下写稿演示截图 商业模式上，Leapility围绕CAF生态圈，形成"Agent OS +专家Agent交易"多元营收结构。用户可按需自助搭建Agent，或通过认证服务商、专家市场采购定 制化Agent及服务，实现从个人专业版、团队版到企业级部署的全场景覆盖。平台通过"变现激励+社区驱动+生态合作"组合模式，持续沉淀专家Agent，为行 业知识高效流通与资产变现提供帮助。 Leapility通过 ...

7 月 3 日，由 Meta 主办的年度业务消息盛会 Conversations 2025 首次在中国落地，于深圳举行。本次大 会以"开启对话，连接世界"为主题，聚焦 WhatsApp、Messenger 和 Instagram 三大核心产品生态在全球 商业拓展中的实践路径与未来趋势，吸引了众多来自技术、品牌、电商等行业的头部代表共聚一堂，围 绕"对话驱动全球业务增长"展开深度交流。Meta 公司首席执行官马克·扎克伯格亦通过视频，向与会嘉 宾分享自己的"对话与增长"战略思路。 作为全球领先的跨境电商独立站 SaaS 平台，店匠科技(Shoplazza)受邀参与峰会，并出席主题圆桌讨论 环节。店匠科技中国区商务负责人张扬与阿里云资深产品设计师徐涛一同，探讨如何借助消息链路，构 建高效、智能的品牌出海新路径。 围绕"对话即服务"的应用场景，张扬分享了店匠商户在实践中的三大关键成效：转化率、连带率与复购 率全面提升。 "我们服务的商户涵盖家具、美妆、时尚、美瞳等多个类目，这些高客单价或高度个性化的品类往往需 要更强的消费者沟通与品牌信任。"张扬介绍道，"即时的深度沟通让商家更高效地理解用户需求，推动 转化在短时间 ...

图片来源： Anthropic 据 TechCrunch 消息， 亚马逊云科技（ AWS ）将于下周推出 AI 智能体市场， Anthropic 已成为其合 作伙伴之一。AWS Agent 市场将于 7 月 15 日在纽约市举行的 AWS 峰会上推出。 如今 AI Agent 无处不在。硅谷的每位投资者都看好开发 AI Agent 的初创公司 ——尽管对于 AI Agent 的确切定义仍存在分歧。 这个术语有些模糊 ，通常被用来描述能够自主决策和执行任务的计 算机程序，例如通过后端 AI 模型与软件交互。 OpenAI 和 Anthropic 等 AI 巨头正将其宣传为科技界的下一件大事。然而， AI Agent 的分发面临挑 战，因为大多数公司都是孤立地提供它们。 AWS 似乎正通过这一新举措来解决这个问题。 该公司的专属 Agent 市场将允许初创企业直接向 AWS 客户提供其 AI Agent 。消息人士称，该市场还 将允许企业客户根据需求在一个平台上浏览、安装和寻找 AI Agent 。 这可能会为 Anthropic， 以及其他 AWS 智能体市场合作伙伴——带来显著的增长动力。 Anthropic ...

软件ETF跟踪的是软件指数，该指数由中证指数有限公司编制，从沪深市场中选取业务涉及软件开发、 信息技术服务等领域的上市公司证券作为指数样本，以反映中国软件行业上市公司的整体表现。该指数 成分股主要集中在计算机软件及相关服务领域，具有较高的成长性和创新性特征。 华泰证券指出，6月软件开发行业景气指数为21.4，有所回升。5月软件业务收入同比增速连续3个月回 升至11.2%，其中信息安全产品、信息技术服务、工业软件收入同比增速均呈现改善。前瞻指标显示， 软件业用电量MA12同比趋势回升，与行业收入增长形成正向关联。此外，AI Agent渗透率进入"奇点时 刻"（约7%），To B应用有望加速放量，或将推动AI产业链景气上行。从细分领域看，通信设备行业景 气指数达60.1，5月光电子器件产量同比小幅回正（+0.9%），移动通信基站设备产量同比增速在Q2明 显回升至7.8%。服务器领域，BMC芯片龙头信骅5月营收同比+74.6%，机壳龙头勤诚营收同比 +46.9%，显示硬件基础设施需求保持强劲。 （文章来源：每日经济新闻） 注：如提及个股仅供参考，不代表投资建议。指数/基金短期涨跌幅及历史表现仅供分析参考，不预示 未 ...

Core Viewpoint - PresentAgent is a multimodal AI agent designed to automatically convert structured or unstructured documents into video presentations with synchronized voiceovers and slides, aiming to replicate human-like information delivery [1][3][22]. Group 1: Functionality and Process - PresentAgent generates highly synchronized visual content and voice explanations, effectively simulating human-style presentations for various document types such as business reports, technical manuals, policy briefs, or academic papers [3][21]. - The system employs a modular generation framework that includes semantic chunking of input documents, layout-guided slide generation, rewriting key information into spoken text, and synchronizing voice with slides to produce coherent video presentations [11][20]. - The process involves several steps: document processing, structured slide generation, synchronized subtitle creation, and voice synthesis, ultimately outputting a presentation video that combines slides and voice [13][14]. Group 2: Evaluation and Performance - The team conducted evaluations using a test set of 30 pairs of human-made "document-presentation videos" across various fields, employing a dual-path evaluation strategy that assesses content understanding and quality through visual-language models [21][22]. - PresentAgent demonstrated performance close to human levels across all evaluation metrics, including content fidelity, visual clarity, and audience comprehension, showcasing its potential in transforming static text into dynamic and accessible presentation formats [21][22]. - The results indicate that combining language models, visual layout generation, and multimodal synthesis can create an explainable and scalable automated presentation generation system [23].

Core Insights - The rapid development of AI Agents has ignited a trend of "everything can be an Agent," particularly evident in the competitive landscape of model development and application [1][2][10] - Major companies like OpenAI, Google, and Alibaba are heavily investing in the Agent space, with new products emerging that enhance user interaction and decision-making capabilities [2][7][8] - The evolution of AI applications is categorized into three phases: prompt-based interactions, workflow-based systems, and the current phase of AI Agents, which emphasize autonomous decision-making and tool usage [17][19] Group 1: Model Development - The AI sector has entered a "arms race" for model development, with significant advancements marked by the release of models like DeepSeek, o3 Pro, and Gemini 2.5 Pro [5][6][14] - The introduction of DeepSeek has demonstrated that there is no significant gap between domestic and international model technologies, prompting major players to accelerate their model strategies [6][10] - The focus has shifted from "pre-training" to "post-training" methods, utilizing reinforcement learning to enhance model performance even with limited labeled data [11][13] Group 2: Application Development - The launch of OpenAI's Operator and Deep Research has marked 2025 as the "Year of AI Agents," with a surge in applications that leverage these capabilities [7][8] - Companies are exploring various applications of AI Agents, with notable examples including Cursor and Windsurf, which have validated product-market fit in the programming domain [9][21] - The ability of Agents to use tools effectively has been a significant breakthrough, allowing for enhanced information retrieval and interaction with external systems [20][21] Group 3: Challenges and Opportunities - Despite advancements, AI Agents face challenges such as context management, memory mechanisms, and interaction with complex software systems [39][40] - The future of Agent applications may involve evolving business models, potentially shifting from subscription-based to usage-based or outcome-based payment structures [40][41] - The industry is witnessing a competitive landscape where vertical-specific Agents may offer more value due to their specialized knowledge and closer user relationships [42][46]

AWS is launching an AI agent marketplace next week with Anthropic as a partner | TechCrunch https://t.co/2SX3uNfJDm ...

Remember the AI agents meta on SOL and Base?What a time to be alive. ...

[Music] hi everyone. Thank you for uh coming to our talk. Uh so he was kind enough to already introduce us.Um so I'm the CEO. Matthew was the first person who joined us. Uh if any difficult questions, please direct it towards Matt.Um now if you think about the three major categories of of software engineering at least as we see it there's three things that show up to me the system design where you think about you know how do you actually architect a system a lot of the the talks we saw in this uh track have ...