--- 格式版本: 2 标题: "[Podcast] Achieving quality excellence with AI" 原文链接: "https://blog.se.com/digital-transformation/artificial-intelligence/2026/09/07/podcast-achieving-quality-excellence-with-ai/" 发布日期: "2026-09-07" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:configured_publication_date_rule" 发布时间证据: "schneider-blog-ymd-date text:scrape: 2026/09/07" 发布时间校准原因: "信源发布日期识别规则直接确认发布时间" 发布时间校准置信度: "high" 发布时间候选数量: 1 发布时间严格候选数量: 1 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-09-07T23:49:10+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-09-07T23:48:51+08:00" 入库时间: "2026-09-07T15:49:55.600Z" 来源平台: "Schneider Electric Blog 搜索" 搜索渠道: "source_template" 搜索词: "https://blog.se.com/?s=AI%20Rack" 匹配关键词: - "AI Rack" - "AI" 相关厂家: [] 相关专家: [] 内容类型: "网页" 抓取工具: "Free Fetch + Defuddle" 清洗工具: "Defuddle Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 19 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "正文主线是施耐德电气播客对AI辅助质量管理和客户体验的泛化介绍，与超节点、AI Rack及机架级基础设施无关。来源为厂商官方博客，但内容偏宣传性播客摘要；历史证据中未见重复事件，也未提供可核验的新架构、标准、工程数据、产品发布、客户部署或量产时间表。仅提及数据、模型、质量本体和工作流等概念，缺少基础设施规格与技术机制，命中通用AI应用弱相关否决。" AI质检模型: "gpt-5.6-sol" AI质检时间: "2026-09-07T23:50:05+08:00" AI主题相关性: 0 AI来源权威性: 9 AI新颖性: 2 AI技术细节: 1 AI商业部署信号: 0 AI完整性: 7 AI评分提示词版本: "v17-精简生产版" AI评分提示词SHA256: "48fb9777f386026761b4873eaff30807694fb11e9b352d7c69bf2dfde750cc7d" AI评分知识库版本: "knowledge_base_v1-20260819+runtime.86" AI评分知识库SHA256: "16cb084764aab70def3967e3f9c4438de00331dbb25a3163c5d909a9cb960893" AI评分知识库检索词: "[\"AI Rack\",\"https://blog.se.com/?s=AI%20Rack\",\"Intel\",\"www.podbean.com/player-v2\",\"te4x2-1b4eef9-pb\",\"pb6admin\",\"f6f6f6\",\"open.spotify.com/episode/6ZnjGD2Q4dC4S4Bd4G3Bsf\",\"tl-fCEUZS8eixq0I2iyKEw\",\"Vfj0etH-rD8\",\"IvlQ5nA_6UVXrKrA\"]" AI评分知识库命中: "[{\"id\":\"historical-jun-042\",\"title\":\"AI Rack/机柜级超节点架构，详细列出Vera Rubin/GB200 NVL72规格、NVLink 6互连、HBM3e、液冷与供电设计，具备明确的产品化与\",\"sourceType\":\"curated_item\",\"time\":\"2026-06\",\"matchedTerms\":[\"AI Rack\"],\"rank\":-7.181919122409135},{\"id\":\"july-correct-0012\",\"title\":\"Microsoft to deploy AMD Helios rackscale solution to support inference workloads and Azure services\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"AI Rack\"],\"rank\":-5.786371094001754},{\"id\":\"july-correct-0081\",\"title\":\"AAI 2026: 6th Gen AMD EPYC Server CPUs Power the Agentic Data Center\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"Intel\"],\"rank\":-5.273555689692019},{\"id\":\"july-correct-0062\",\"title\":\"Why AI Racks Need an Open Signal Conditioning Standard\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"AI Rack\"],\"rank\":-5.196598508853131},{\"id\":\"historical-may-024\",\"title\":\"OpenAI、Microsoft等围绕MRC协议构建更大规模AI以太网训练网络\",\"sourceType\":\"curated_item\",\"time\":\"2026-05\",\"matchedTerms\":[\"Intel\"],\"rank\":-4.8559676183194185}]" AI摘要: "施耐德电气客户满意度与质量高级副总裁Brigitte Begasse在AI at Scale播客中探讨AI在质量与客户体验领域的应用，强调AI并非替代质量专家，而是帮助扩展专业能力、加速学习，并把洞察更快转化为行动。" AI摘要模型: "ali-deepseek-v4-flash" AI摘要时间: "2026-09-07T21:43:52.319Z" 采集批次: "2026年9月7日22点57分10秒" 采集批次ID: "20260907-225710-732" 去重键: "https://blog.se.com/digital-transformation/artificial-intelligence/2026/09/07/podcast-achieving-quality-excellence-with-ai" --- “AI is not replacing quality expertise. It is helping us scale learning, scale expertise, and turn insight into action faster.” In this episode of the **AI at Scale Podcast**, **Brigitte Begasse**, Senior Vice President of Customer Satisfaction and Quality at Schneider Electric, explores what AI really changes in two areas where the stakes are high: quality and customer experience. ## Why quality excellence with AI matters Quality is more than inspections and defect fixing. It is a promise made to customers every day – that a product will be safe, compliant, reliable, and deliver the right experience across its entire life cycle. Behind that promise sit enormous volumes of data: test results, factory data, supplier information, customer feedback, and field reports. No team can analyze all of it fast enough. That is where AI comes in. Brigitte explains how AI connects these scores of signals, spots patterns across countries and products, and surfaces risks earlier. But data alone is not enough. She describes data as the “fourth dimension” of the organization, and makes the case that value comes only when good data meets the right models, the right quality ontology, and human expertise. ## From insight to action The goals are speed and business outcomes. The real question is not whether AI can produce an insight, but how quickly that insight becomes an action. And that action becomes value for the customer. From product design to the shop floor to listening at scale across customer channels, AI helps experts do more, more consistently. It does not replace human judgement. Accountability stays human. **In this episode, you will learn:** ✔ why quality is a promise, not just an inspection step ✔ how AI helps predict and prevent risks earlier, not just detect them ✔ why data needs the right models and ontology to create trusted insight ✔ how AI scales expert knowledge instead of replacing experts ✔ why transformation is about workflows and ownership, not just tools ✔ what predictive quality looks like — and why it matters for customers **Listen to the AI at Scale podcast** Listen to **Brigitte Begasse in Achieving quality excellence with AI.** Subscribe to the show on your preferred streaming platform (, [Spotify](https://open.spotify.com/episode/6ZnjGD2Q4dC4S4Bd4G3Bsf?si=tl-fCEUZS8eixq0I2iyKEw)), or watch on [YouTube](https://www.youtube.com/watch?v=Vfj0etH-rD8&list=PLa7UGrWOTyjlY6cTHzqoXJiNh__E0J3I7). ### Like what you hear? - Visit our [AI at Scale website](https://www.se.com/ww/en/work/solutions/artificial-intelligence/) to discover how do we transform energy management and industrial automation with artificial intelligence technologies to create more sustainable solutions. - Listen to the [other episodes of the AI at Scale podcast](https://aiatscale.podbean.com/) or watch them on [YouTube](https://youtube.com/playlist?list=PLa7UGrWOTyjlY6cTHzqoXJiNh__E0J3I7&si=IvlQ5nA_6UVXrKrA).