SPS Commerce (SPSC) FY Conference June 10, 2025 03:40 PM ET Speaker0 Alright, everyone. Thanks for being here. We're gonna get started with SPS Commerce. We have the pleasure of Chad Collins, CEO Kim Nelson, CFO of SPS Commerce. I'm Will Jelison. I cover vertical and back office software for Davidson of which SPS, is one. So thanks for being here. Speaker1 Thank you. Speaker0 I figured it makes sense to start out this conversation with maybe a couple of minutes overview on who SPS is, the problem you solve, ...

Revvity (RVTY) FY Conference Summary Company Overview - **Company**: Revvity (formerly PerkinElmer) - **Industry**: Life Sciences Tools and Diagnostics Key Points and Arguments Market Environment and Company Adaptation - The current market is dynamic with uncertainties due to policy changes, tariffs, and challenges in pharma, biotech, and academia sectors [3][4][5] - Revvity's diverse portfolio has demonstrated resilience amidst these challenges, with 60% of revenue now coming from diagnostics and software [4][5][8] Financial Performance and Growth - Revvity's growth rate is at the top end of its publicly traded peer group, with a long-range plan (LRP) growth target of 6-8%, compared to 3-5% previously [4][7] - The company has shifted to a recurring revenue model, with over 80% of revenue now from recurring sources, improving margins from 18-20% to 28% [7][8] - Organic growth guidance for the year is set at 3-5%, with confidence in achieving this despite market uncertainties [9][12] Life Sciences Segment Challenges - The life sciences segment faces challenges due to funding shifts towards clinical work, impacting preclinical discovery [14][15] - Revvity's differentiated product portfolio in consumables is expected to maintain growth despite these challenges [15][20] Software Business - Revvity's software business is unique, functioning as an ERP for researchers, with 48 out of the top 50 pharma companies using its software [26][28] - The software segment is expected to grow significantly, contributing to overall margin improvement [56] Diagnostics and Growth Opportunities - Immunodiagnostics represent a significant growth opportunity in the U.S., with current market penetration at 15-20% compared to a historical 35-40% [30][31] - The company is focusing on expanding its offerings in reproductive health and rare disease testing, leveraging partnerships for growth [40][41] Competitive Landscape in China - Revvity faces intense competition in China, but differentiates itself through proprietary assays and a focus on complex diseases [35][36] - The company is adapting to local market conditions and regulatory environments to maintain growth and profitability [36][39] Capital Allocation and M&A Strategy - Revvity has been active in M&A, completing 13 acquisitions in 22 months to enhance its portfolio [60][62] - Current capital allocation focuses on share buybacks, with a balanced approach to future M&A opportunities [64][68] Long-term Outlook - The company aims for mid-30s operating margins in a normalized market environment, with equal opportunities for margin expansion across life sciences and diagnostics [54][56] - Revvity's strong portfolio and execution strategy position it well for long-term growth despite current macroeconomic challenges [72][74] Additional Important Insights - The company emphasizes innovation and automation in its product offerings to enhance researcher productivity, especially in a budget-constrained environment [47] - Revvity's software and diagnostics segments are seen as critical to its long-term success, with ongoing efforts to improve customer stickiness and market penetration [25][28][70]

什么是算法? 今天，"算法"这个词已为越来越多的人所熟知。从微信上传递文件和图片，到百度、谷歌等搜索引擎上 的网页排名，再到收发电子邮件，我们几乎没有一天不与算法打交道。 脸书很少公开谈论其算法的具体运作方式。事实上，在单个用户的层面上，它自己也不知道是怎么运作 的。算法产生的结果对每个用户来说都是独一无二的，就像他们的指纹一样。 那么，什么是算法呢? 如果你去问计算机科学家，他们会告诉你：算法就是用计算机语言编写的一串指令，它接受输入，对输 入的信息执行一些可重复的运算，然后提供输出。 一个简单的例子是冒泡排序算法(或许你在学计算机语言的时候，自己就编过这样的程序)，你向它输入 一串数字，让它按从小到大的顺序重新排列。它首先比较前两个数字。如果前一个大于后一个，就将它 们对调。否则，就换到下一对。它会一次又一次地循环，直到不需要任何交换为止，这时它就会输出一 个排好序的数字列表。如果你在网上购物时按价格从低到高筛选产品，那么冒泡排序算法就会在幕后启 动。 不过，"算法"一词的流行用法正在发生变化：它越来越多地被用来描述计算机所完成的几乎任何事情。 这也包括人工智能(AI)和机器学习领域，在这些领域，算法的步 ...

6月9日，由法国和哥斯达黎加共同主办的第三届联合国海洋大会在法国尼斯开幕。期间，中国国家海洋 信息中心牵头举办"启智海洋：创新科学引领行动，共促可持续的未来"边会，自然资源部代表中国面向 国际公开发布了中国全球海洋融合数据集1.0。中国国家海洋信息中心研究员于婷表示，本次发布的中 国全球海洋融合数据集CGOF1.0，它基本上涵盖了国内外40多种不同的数据来源，也融入了中国的自主 海洋观测，时间跨度可以长达60年。它的空间分辨率达到了10公里。它融合了深度学习、迁移学习、机 器学习等先进的AI智能技术。它的精度较国外主流的一些数据集质量都有所提升。(央视新闻) ...

Core Insights - Quantitative stock investment is expected to perform exceptionally well in 2025 after years of stagnation, driven by models based on factors and machine learning that have shown strong performance amid market volatility and political noise [1][6] Group 1: Strategy Recovery - Traditional long/short factor models and newer machine learning-based strategies are experiencing a revival, with the global bottom-up stock factor strategy rising over 9% this year, successfully navigating market volatility [2][3] - The top-down factor indices covering regions like Europe, the US, and Japan have also shown robust growth, particularly value and momentum strategies outside the US [2] Group 2: Regional and Strategy Performance - Europe has been the leading region for factor performance in 2025, with value strategies achieving the best relative and absolute returns, although valuation gaps have narrowed significantly [3] - Machine learning models from Société Générale have performed strongly, with a newly launched mean-reversion strategy yielding a return of 4.1%, outperforming basic reversal models [3] Group 3: Investment Themes and Strategy Outlook - Société Générale is optimistic about defensive stock income strategies, focusing on companies with strong balance sheets and high dividend yields, particularly in utilities, telecom, and energy sectors [4] - The US small-cap value strategy, excluding distressed stocks, has outperformed benchmark indices, emphasizing the importance of balance sheet strength as credit conditions tighten [4] - The "strong balance sheet" trade is supported as an alternative hedging strategy against high-yield credit risk, maintaining positive growth in 2025 [4] Group 4: Outlook for the Second Half of 2025 - Despite the strong performance of European value strategies, a cautious outlook is held for the second half of 2025 due to rising market volatility and valuation spreads nearing historical norms [5] - The easy gains from European value stocks may be over, influenced by geopolitical uncertainties and increasing earnings risks [5]

在宁波调研期间，记者深刻体会到，数字技术并不冰冷，而是为金融服务注入了实打实的温度。宁波银 行的"财资大管家"与"外汇金管家"系统，优化了企业资金管理，提升了资金使用效率。其"波波知了"数 据平台在法律咨询、税务咨询等方面提供了多元化服务，尤其是海外拓客助手功能，为外贸企业拓展海 外市场提供了有力支撑。 在数字化浪潮中，金融机构纷纷布局数字金融，推动金融服务效率提升和产品创新。数字技术赋能的服 务已突破传统信贷业务范畴，向全方位服务模式转变，成为促进民营企业高质量发展的关键力量。 另一方面，金融机构应加大技术研发投入，与科技公司或高校合作，优化智能系统算法与模型，提升其 在复杂风险评估和精准融资匹配方面的能力。借助先进的人工智能、机器学习等技术，智能系统能够更 精准地分析企业数据，提供个性化融资方案，满足企业多元化融资需求。 此外，金融机构还需依据企业的具体需求，量身定制融资方案，关注企业在非金融领域的需求和行业共 性问题，提供更贴合实际、更周到的服务，实现金融服务温度与深度的并重。宁波通商银行的科创孵化 基地就是一个典型案例，其依托数字化运营体系，汇聚众多投资和服务机构资源，形成了一个开放、合 作、共赢的科 ...

Core Viewpoint - The article discusses the challenges in semiconductor parameter extraction due to the complexity of device models and the limitations of traditional optimization algorithms, introducing Keysight's ML Optimizer as a revolutionary solution to enhance efficiency and accuracy in this process [1][4]. Group 1: Challenges in Semiconductor Parameter Extraction - The complexity of semiconductor device models has made parameter extraction increasingly challenging, with traditional optimization algorithms often getting stuck in local optima due to unclear gradient changes [1]. - The presence of numerous interrelated parameters in modern semiconductor models leads to inefficiencies in traditional methods, requiring engineers to break down the extraction process into lengthy sub-steps, which can take days or even weeks [1]. Group 2: Introduction of ML Optimizer - Keysight has launched the ML Optimizer, a machine learning-based global optimizer that simplifies the parameter extraction process by synchronously handling vast amounts of data in a single step, reducing the extraction time from days to just hours [2][4]. - The ML Optimizer excels in navigating non-convex parameter spaces, utilizing advanced machine learning algorithms to find global optima more accurately, thereby improving the precision of parameter extraction and the consistency of overall fitting [4]. Group 3: Live Demonstration and Applications - A live demonstration is scheduled to showcase the ML Optimizer's effectiveness in various device modeling tasks, including diodes, GaN HEMTs, MOSFETs, and BJTs, with interactive elements and prizes for participants [4][6]. - The event will feature experts from Keysight, including application engineers and product managers, who will discuss the application of artificial neural networks and the ML Optimizer in device modeling [8][11].

据介绍,该产品成立于2022年10月,迄今运作时间超两年半,历经多个市场波动周期,自成立以来净值增长率 为10.33%,年化收益率达到3.80%,最大回撤仅-0.32%,其投资策略和业绩表现受到业界和客户的广泛认 可。 6月5日,由财视中国主办的第十八届"银行业·介甫奖评选"在上海举行。平安理财凭借专业精进的投研能 力、稳健优异的业绩表现等荣获"杰出银行理财子公司",旗下的启元策略(360天持有)1号获评"卓越创新 银行理财产品"。 作为在资管行业发展新格局大背景下成立的银行理财公司,平安理财以打造"国内品类最全的开放式理财 平台"为目标,持续提升专业投研、产品体系、渠道经营、运营服务、风险管理方面"五位一体"的能力,构 建多元化人才队伍和数据科技创新"双擎驱动"竞争优势,打造以"稳"为特色、聚焦绝对收益目标的产品 体系,致力于以更强的责任担当、更扎实的投研能力服务实体经济高质量发展,守护老百姓的钱袋子。 本届"介甫奖"评选中,平安理财旗下的启元策略(360天持有)1号固收类产品备受关注。"启元策略360天1 号A"是以绝对收益为目标的固收类理财产品,其以稳健资产打底、融入固收量化策略,基于机器学习和量 化模 ...

如果您希望可以时常见面，欢迎标星收藏哦~ 来源：内容 编译自 ieee 。 对于那些喜欢支持弱者的人来说，最新的MLPerf基准测试结果可能会令人失望：Nvidia 的GPU仍 然占据主导地位再次。这包括在最新、最苛刻的基准测试中，对Llama 3.1 403B 大型语言模型进 行预训练时，所展现出的顶级性能。即便如此，基于最新AMD GPU MI325X 构建的计算机在最 流行的 LLM 微调基准测试中，其性能与Blackwell 的前代产品 Nvidia H200 相当。这表明 AMD 落后了Nvidia一代。 MLPerf训练是MLCommons联盟举办的机器学习竞赛之一。"AI 性能有时就像狂野西部。MLPerf 致力于打破这种混乱，" Nvidia 加速计算产品总监Dave Salvator表示。"这并非易事。" 本次比赛包含六个基准测试，每个基准测试分别针对一个与行业相关的机器学习任务。这些基准测 试包括内容推荐、大型语言模型预训练、大型语言模型微调、机器视觉应用的目标检测、图像生成 以及用于欺诈检测和药物研发 等应用的图节点分类。 大型语言模型预训练任务是最耗费资源的，而本轮更新后更是资源密集。 ...

【环球网科技综合报道】6月5日消息，据外媒报道，苹果公司正为AirPods耳机开发一系列新功能，这些功能有望在下周举行的WWDC 2025全球开发者大会 上正式亮相，旨在从交互控制、健康感知、内容创作及教育场景等多个维度提升用户体验。 在内容创作方面，苹果正为AirPods开发类似iPhone 16"音频混音"（Audio Mix）技术的"录音室级"麦克风模式。该功能借助机器学习技术，能够分离人声与 背景音，从而为内容创作者提供便携式麦克风，助力其创作。 此外，在教育场景中，苹果致力于改善课堂环境里AirPods与共享iPad的配对体验。新功能将大幅减少手动操作步骤，降低设备连接的复杂度，为多学生共 用设备的教育场景提供更高效、流畅的支持。（纯钧） 在交互控制方面，苹果持续推进AirPods的交互升级。继去年推出头部动作接听电话功能后，公司正开发更为丰富的头部控制方案。未来，用户或许只需通 过点头或摇头的动作，即可实现对"对话感知"音量的调节，并且在完成调节后，系统会自动恢复原有的降噪设置，无需再通过按压或滑动耳柄来操作。同 时，苹果还计划引入一项新功能，用户点击AirPods耳柄即可触发iPhone或iPa ...