--- 格式版本: 2 标题: "Agentic AI Using Open Source Models: Finetuning, Deployment and Chip Design Case Studies S81702 | GTC San Jose 2026" 原文链接: "https://www.nvidia.com/gtc/session-catalog/sessions/gtc26-s81702/" 发布日期: "2026-07-31" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:scrape:provider_published_at" 发布时间证据: "provider publishedAt: 2026-07-31" 发布时间校准原因: "规则确认唯一严格发布时间，来源 scrape:provider_published_at" 发布时间校准置信度: "high" 发布时间候选数量: 6 发布时间严格候选数量: 2 发布时间原页读取状态: "原页面已读取" 发布时间未找到原因: "" 发布时间校准时间: "2026-07-31T21:46:35+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: "2026-07-31T21:46:24+08:00" 入库时间: "2026-07-31T13:46:35.833Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://www.nvidia.com/gtc/" 匹配关键词: - "deployment" - "performance" 相关厂家: - "NVIDIA" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 10 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "页面仅为GTC固定入口，无任何关于超节点/AI Rack/机柜级系统的实质内容，仅含导航和cookie设置，不符合主题要求。" AI质检模型: "deepseek-v4-flash" AI质检时间: "2026-07-31T21:48:00+08:00" AI主题相关性: 0 AI来源权威性: 15 AI新颖性: 0 AI技术细节: 0 AI商业部署信号: 0 AI完整性: 0 采集批次: "2026年7月31日21点46分24秒" 采集批次ID: "20260731-214624-519" 去重键: "https://www.nvidia.com/gtc/session-catalog/sessions/gtc26-s81702" --- Title: Agentic AI Using Open Source Models: Finetuning, Deployment and Chip Design Case Studies S81702 | GTC San Jose 2026 URL Source: https://www.nvidia.com/gtc/session-catalog/sessions/gtc26-s81702/ Published Time: Fri, 31 Jul 2026 13:46:21 GMT Markdown Content: Visit your regional NVIDIA website for local content, pricing, and where to buy partners specific to your country. 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