单词学习：![[2026051160836175.mp3]]

新闻播报：![[2026051151239923.mp3]]

淘宝深度整合通义千问AI，开启对话式智能购物新模式

简报：

• 阿里巴巴将通义千问AI与淘宝深度整合，接入淘宝和天猫超40亿款商品，通过对话式交互替代传统关键词搜索。
• 用户在通义千问应用中可通过与AI智能体对话，直接完成商品浏览、比价、下单，并获取物流调度到售后服务的全方位支持。
• 淘宝APP内同步上线由通义千问赋能的AI购物助手，可根据用户偏好智能推荐商品，并提供虚拟试穿和30天价格走势追踪等实用功能。
• 该模式将人工智能技术深入嵌入真实交易全流程，凸显了国内电商与海外平台在AI应用策略上的发展差异。

相关链接：

• 阿里巴巴推出通义千问 AI，革新淘宝购物体验

Taobao Deeply Integrates Tongyi Qianwen AI, Ushering In a New Era of Conversational Smart Shopping 🛍️🤖

Brief:

• Alibaba has deeply integrated Tongyi Qianwen AI with Taobao, connecting it to more than 4 billion products across Taobao and Tmall, and replacing traditional keyword searches with conversational interactions.
• Within the Tongyi Qianwen app, users can directly browse products, compare prices, and place orders through conversations with AI agents, while also receiving comprehensive support ranging from logistics coordination to after-sales service.
• An AI shopping assistant powered by Tongyi Qianwen has also been launched inside the Taobao app, where it can intelligently recommend products based on user preferences and offer practical features such as virtual try-ons and 30-day price trend tracking.
• This model embeds artificial intelligence deeply into the entire real-world transaction process, highlighting the differences in AI application strategies between domestic e-commerce platforms and their overseas counterparts. 🚀

Related Link:

• Alibaba Launches Tongyi Qianwen AI, Transforming the Taobao Shopping Experience

联发科台湾首建研发资料中心，全面推进AI发展战略

简报：

• 联发科在台湾地区正式设立了首座研发资料中心。
• 该设施的建立旨在进一步加速联发科在人工智能（AI）领域的战略布局与发展。

相关链接：

• 联发科在台设立首座研发资料中心，加速 AI 布局

MediaTek Establishes Its First R&D Data Center in Taiwan, Fully Advancing Its AI Development Strategy 🚀

Brief:

• MediaTek has officially established its first R&D data center in Taiwan.
• The facility is intended to further accelerate MediaTek’s strategic expansion and development in the field of artificial intelligence (AI) 🤖.

Related Link:

• MediaTek Establishes Its First R&D Data Center in Taiwan to Accelerate AI Expansion

谷歌Gemini API文件搜索迎大升级：多模态RAG支持原生图文解析与页面级溯源

简报：

• 谷歌宣布对Gemini API的文件搜索功能进行重大升级，为开发者提供更完善的多模态检索增强生成（RAG）能力。
• 新版功能基于Gemini Embedding2模型构建，开发者无需搭建复杂的向量数据库，即可在API内部完成从数据上传到信息检索的完整RAG工作流。
• 系统具备统一的多模态嵌入能力，可原生识别和处理PDF、文档及图片等视觉信息，解决了传统RAG系统无法有效读取图表、设计图等非文本内容的痛点。
• 新增自定义元数据过滤功能，开发者可通过添加部门、时间、分类等标签条件进行预设过滤，使AI输出的回答更加聚焦。
• 支持页面级引用溯源，AI生成答案时会明确标注信息来源的具体文档页码，大幅提升内容核实效率与透明度。
• 目前该增强版文件搜索功能已向全球开发者开放，支持通过Google AI Studio或Google Cloud平台接入体验。

相关链接：

• Google 升级 Gemini API 文件搜索：多模态 RAG 能力实现全方位跨越

Google Gemini API File Search Gets a Major Upgrade: Multimodal RAG Now Supports Native Image-Text Parsing and Page-Level Source Tracing 🚀

Brief:

• Google has announced a major upgrade to the file search capabilities of the Gemini API, providing developers with more comprehensive multimodal retrieval-augmented generation (RAG) features.
• Built on the Gemini Embedding2 model, the new functionality allows developers to complete the entire RAG workflow—from data upload to information retrieval—directly within the API, without the need to build a complex vector database.
• The system offers unified multimodal embedding capabilities and can natively recognize and process visual information in PDFs, documents, and images, addressing a key limitation of traditional RAG systems that struggle to effectively interpret non-text content such as charts and design diagrams. 🖼️
• A new custom metadata filtering feature allows developers to preset filtering conditions by adding tags such as department, time, and category, enabling AI-generated responses to be more focused.
• Page-level citation tracing is now supported, allowing AI-generated answers to clearly indicate the exact document page where the information originated, greatly improving verification efficiency and transparency. 🔎
• The enhanced file search feature is now available to developers worldwide and can be accessed through Google AI Studio or the Google Cloud platform.

Related link:

• Google Upgrades Gemini API File Search: Multimodal RAG Capabilities Achieve a Comprehensive Leap