SAN FRANCISCO, April 24, 2025 (GLOBE NEWSWIRE) -- Redis, the world's fastest data platform, and UiPath (NYSE:PATH), a leading enterprise automation and AI software company, today expanded their collaboration toward furthering agentic automation solutions for customers. Redis, a UiPath Technology Alliance partner, has played a crucial role in increasing the speed and efficiency of UiPath's Automation Suite. Redis powers UiPath Orchestrator's high-availability add-on (HAA), an on-premises offering that improv ...

Harvey 绝对是法律场景落地最成功的 AI 企业了。 成立于 2022 年，客户数量从 2023 年的 40 家增长到 2024 年的 235 家，遍布 42 个国家；在美国《法律周刊》评选的前 100 家律所中，有 28 家正在使用 Harvey。 2024 年 ARR 达到 5000 万美元，今年年初预计 8 个月内将达到 1 亿美元，2 月份拿到了红杉资本领投的 3 亿美元 D 轮融资，公司估值达到 30 亿美元 。 简单说的话， Harvey 现在的收入与 AI 搜索当红炸子鸡 Perplexity 相当。 在前不久 福布斯发布的 2025 AI 50 榜单 中，Harvey 是法律领域上榜的为数不多的公司之一。Harvey 目前已经能够实现自动处理从文件审查到客户沟通 的整个法律流程，几乎能替代一整个初级律师团队。 近段时间，Harvey 的创始人兼 CEO Winston Weinberg 以及产品负责人 Aatish Nayak 接受了多家播客节目的访谈，在访谈节目中，两人详细地分享了包 括 Harvey 的顶层战略方向设计、法律类 AI 产品如何实现商业化落地、法律类 Agentic wo ...

Financial Data and Key Metrics Changes - Total revenue for Q1 2025 was $263 million, up 3% year-over-year [36] - Cloud revenue increased 21% to $94 million, while services revenue declined 8% to $121 million [37] - RPO ended the quarter at approximately $1.9 billion, up 25% year-over-year and 6% sequentially [38] - Adjusted operating profit was $91 million with an adjusted operating margin of 34.7%, up over 340 basis points year-over-year [40] - Adjusted earnings per share (EPS) for Q1 was $1.19, up 16%, while GAAP EPS was 85 cents, down 1% [41] Business Line Data and Key Metrics Changes - The company experienced a 25% year-over-year increase in RPOs, driven by strong demand for mission-critical solutions [22] - Approximately 50% of new cloud bookings in Q1 were generated from net new logos, indicating strong demand for products [71] - Services team completed over 100 go-lives for customers in Q1, showcasing operational effectiveness [25] Market Data and Key Metrics Changes - The addressable market is forecasted to grow at a double-digit CAGR for the next several years, indicating robust market potential [15] - Competitive win rates remained consistent at about 70%, reflecting strong market positioning [24] - The company has established healthy footprints across diverse sectors including retail, grocery, life sciences, and technology [23] Company Strategy and Development Direction - The company is focused on organic innovation and capital allocation strategy to expand its addressable market [14] - Investment in sales and marketing is prioritized to drive growth and capitalize on new product offerings [64] - The launch of new products like Enterprise Promise and Fulfill aims to optimize B2B order fulfillment, addressing evolving customer needs [26] Management's Comments on Operating Environment and Future Outlook - Management expressed caution regarding near-term services revenue growth due to macroeconomic uncertainties [21] - The company remains optimistic about its position in the market and long-term growth opportunities despite current challenges [20] - Management reiterated full-year guidance for RPO and total revenue, reflecting confidence in business fundamentals [45] Other Important Information - The company was named Google’s Cloud Business Applications Partner of the Year for supply chain and logistics, highlighting its innovation in the Google Cloud ecosystem [18] - The company ended the quarter with $206 million in cash and zero debt, indicating a strong balance sheet [42] Q&A Session Summary Question: Insights on cloud bookings and RPO dynamics - Management indicated strong pipeline in Q2 and confidence in guidance despite macro uncertainties [59][60] Question: Growth investments and monetization of products - Management plans to invest in sales specialists to drive growth and maintain high win rates [64] Question: Linear progression of bookings and sales activity - Management noted a balanced product portfolio and strong demand across verticals, with high expectations for Q2 [68][71] Question: Resilience of cloud bookings drivers - Management stated that no particular segment is more resilient, but all channels remain important for growth [78][80] Question: Visibility on multi-year ramps and growth trajectory - Management confirmed strong visibility into contract durations and ramp processes, supporting confidence in growth [95][97] Question: FX impact on guidance - Management indicated that FX swings represent less than 1% impact on revenue guidance [104][105] Question: Strength of large deals in the pipeline - Management reported favorable conditions in the pipeline, with confidence in closure rates compared to last year [111][112]

但 LangChain 创始人 Harrison Chase 对于 OpenAI 在文中的一些观点持有异议，尤其是「通过 LLMs 来主导 Agent」的路线，迅速发表了一篇长文回 应。 Harrison Chase 认为，并非要通过严格的「二元论」来区分 Agent，目前我们看到大多数的「Agentic 系统」都是 Workflows 和 Agents 的结合。理想 的 Agent 框架应该允许从「结构化工作流」逐步过渡到「由模型驱动」，并在两者之间灵活切换。 相比 OpenAI 的文章，Harrison Chase 更认同 Anthropic 此前发布的如何构建高效 Agents 的文章，对于 Agent 的定义，Anthropic 提出了「Agentic 系 统」的概念，并且把 Workflows 和 Agents 都看作是其不同表现形式。 总的来说， 这是大模型派（Big Model）和工作流派（Big Workflow）的又一次争锋， 前者认为每次模型升级都可能让精心设计的工作流瞬间过 时，这种「苦涩的教训」让他们更倾向于构建通用型、结构最少的智能体系统。而以 LangGraph 为代表的后者，强调 ...

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The clinical research arena is experiencing transformative advancements due to the successful application of Generative AI (GenAI) tools, enhancing efficiency and quality in clinical trials [4][6] - Regulatory agencies, including the FDA, are beginning to establish guidelines for the responsible use of AI in clinical studies [6] - The report emphasizes a multi-pronged approach to safeguard efficiency and quality in clinical trials through various AI methodologies [19] Overview - The report highlights the increasing anticipation among industry professionals regarding the potential of AI to improve clinical trials and healthcare [4] - There are numerous opportunities to leverage AI technologies across the clinical trial ecosystem, including design, patient engagement, and regulatory submissions [5] AI Methodologies - Distinction is made between Generative AI, which generates responses based on training data, and agentic AI, which independently handles complex problems [10][11] - A holistic approach is necessary for developing AI frameworks, emphasizing the importance of training, ethical considerations, and human oversight [12][13] Safeguards for AI in Clinical Trials - Five critical categories of safeguards are identified to ensure the safe and efficient use of AI in clinical studies: curating and containerizing data, integrating "human-in-the-loop," harmonization of response, objectivity, and recognizing uncertainty [19][20] - Curating training data is essential to avoid poor-quality responses and ensure reliability in clinical operations [24][25] - The integration of human oversight is crucial to optimize quality and prevent erroneous outputs from AI systems [26][29] Use Cases of AI in Clinical Trials - The report discusses successful applications of AI, including a scientific Q&A chatbot used in a Phase III trial, which improved the efficiency of protocol clarifications and reduced the burden on medical monitors [39][40] - The chatbot's success was attributed to rigorous training, harmonized responses, and the ability to recognize knowledge gaps [41][42]

作者：yongxin 编辑：Siqi Agentic AI 的 3 要素是：tool use，memory 和 context，围绕这三个场景会出现 agent-native Infra 的 机会。 01 . 为什么 Search API 很重要 按照场景和信息需求类型，搜索行为大致可以被分为四类： • 第一类，高频快速查询， 指的是一两步内就能完成的查询。Google 大部分的 query 还是以几个单词为 主，用户得到答案后马上离开，不会进行深入的查询。对于这类查询 Google、Bing 还是最好的应用，新 玩家几乎没有挑战的机会。 • 第二类，研究性质的深入查询， 用户可以和搜索工具反复交流，获取知识。这一类搜索是 LLM 和 LRM 带来的新场景，对应的代表性产品形态分别是 Chatbot 和 Deep research。 Agent 所获取到的信息质量是 agent 推理的起点，虽然 LLM 带来了 perplexity 为代表的 AI answer engine，提供了完全不同于传统搜索引擎的体验，但这些产品仍旧面向的是人类用户，产品逻辑是围 绕人类行为设计的。 在我们 MCP 的研究中发现， ...

随着我们迈入 Agentic 时代，对于各组织机构而言，若要对模型进行扩展以实现高效推理，他们将需要 在从训练到推理的每一个步骤中都遵循扩展流程。在 NVIDIA GTC 2025 上，黄仁勋的愿景以及所发布 的消息聚焦于在从企业信息技术、云计算到机器人技术等各个行业中构建 " AI工厂"。 为了让AI工厂取得成功，NVIDIA持续创新，并提供完整的AI技术栈，包括芯片、系统和软件，以最高 的效率来加速和扩展AI。该公司的方法涵盖了Agentic AI 和 Physical AI 领域。NVIDIA在其整个技术栈 方面做出了以下发布内容： 图片来源：NVIDIA & Counterpoint Research 芯片方面：从计算路线图到硅光子学领域 都有重大消息发布 图片来源：NVIDIA NVIDIA 的芯片产品组合涵盖了中央处理器（CPU）、图形处理器（GPU）以及网络设备（用于纵 向扩展和横向扩展）。 NVIDIA 发布了其最新的 " Blackwell超级AI工厂" 平台 GB300 NVL72，与 GB200 NVL72 相比，其 AI性能提升了 1.5 倍。 NVIDIA 分享了其芯片路线图，这样一 ...

2025年，AI产业化元年已经是箭在弦上，只欠关键场景的"东风"。 iTerms Pro，一个为法务"真干活"的AI智能体。 从越来越多的AI应用自主接入DeepSeek，到Agentic AI（智能体）的崛起，技术和产品形态狂飙，AI 平权化时代来临，似乎也将各行各业的智能化转型推 向了临界点。 在法律 科技 行业，国内头部电子签名产品与解决方案提供商法大大，也以十年积淀给出了自己的答案—— 基于自研法律大模型，发布法务AI智能体产品 iTerms Pro。 深究AI产业化的本质，不难发现：AI的价值不在于炫技，而在于让技术穿透专业场景， 尤其是容错率极低的法务岗位，好的法务AI产品需要做的是 放大专 业价值，从而实现人机协同的效应。 所以，让AI产品化不难，难的是让AI应用帮法务"真干活"。 合规挑战下，智能体"破局" "法务数字化在中大型客户群体中已经落地了很久，但人与AI协同去驱动业务流转的愿景，却还有很长的路要走。" 法大大产品负责人梅容告诉36氪，目前国内 大概有 一半以上的企业都已经完成了合同的数字化管理。 但与此同时，其中的大多数仍困在"流程线上化"的浅水区，大量的非标合同依赖人工审查和驱动， ...

亚马逊云科技 从对话到执行: Agentic 开启新范式 * 2025/03.30 | 北京站 >>>>> 在 AI 的下一个浪潮中,我们不再满足于对话,而是追求行动与执行。这场系 列活动为那些站在 AI 革命前沿的开发者与创业者而生 -- 那些不仅看到 Agentic Al 的技术可能,更能洞察其重塑产业的无限潜能的先行者们。我们 相信,Agent 不仅是技术演进,更是思维与商业模式的全新起点。在这里,你 将获取前沿技术洞察、实战开发经验、商业化路径探索,以及与志同道合者 建立的宝贵连接。我们不仅提供知识和灵感,更通过 Ignite Agent 云创计划 为有远见的创业者提供关键支持 -- 从技术资源、基础设施、专家指导到市 场对接,全方位加速你的 Agent 创新从概念到市场的旅程。现在就行动起 来,未来属于那些不只对话,更敢于执行的创造者。 Multi-Agent框架拆解 借助MCP加速应用开发 © 活动时间:2025年3月30日 0 活动地点:北京市朝阳区颐堤港写字楼18层 品 合作机构: ENP 13特工学审 深 思 間 CAMEL-AI 扫码立即注册 t 会议日程 0 (919 ● 14:00~1 ...

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