"一年前，我说我们站在机器智能爆发的前夜，当时还有很多人问：'真的会爆发吗？'但今天，不再有 人质疑。"近日，亚马逊全球副总裁、亚马逊云科技大中华区总裁储瑞松在接受21世纪经济报道记者独 家专访时笑言。 相比于其他云厂商，AWS的这一策略更偏重于部署与实用。Agentic AI时代，各式各样的Agent为云服 务中的"软件即服务"（Software as Service）注入新内核 。 Gartner预测，到2028年，通过代理型AI自主作出的日常工作决策比例将从2024年的0%提高至15%以 上，包含代理型AI的企业软件应用比例将从2024年的不足1%提高至33%。 而对于身处大中华区最前线的储瑞松来说，他看得更具体。目前，很多企业已在开发、客服、数据处理 等环节开始试水Agentic AI，企业的落地节奏正在迅速拉开差距。 在他看来，Agentic AI火爆的背后，已经集齐了"大模型推理能力""标准协议支撑""低幻觉高效率运 行""多智能体协同"等技术要素。例如最新一代MCP协议（Model Context Protocol）正逐步成为Agent访 问企业数据与调用API的"USB接口"，使智能体真正具备 ...

Core Insights - The article discusses the rapid evolution and changing landscape of the large model industry, highlighting a shift from numerous players to a few dominant ones focusing on capital and technology battles [2][29] - The focus has transitioned from model performance to the practical application of large models in business productivity, with "Agent" technology emerging as a key solution [4][8] Group 1: Industry Trends - The "hundred model battle" of 2023 has evolved into a scenario where the market is dominated by a few players, emphasizing the importance of converting large model capabilities into business value [2][29] - The emergence of Agentic AI is driven by advancements in agent orchestration frameworks and standardized protocols, making it easier to build and deploy agents across various industries [10][19] Group 2: Agentic AI Development - AWS's recent summit emphasized Agentic AI as a transformative technology that allows large models to take proactive actions rather than just responding to prompts [8][10] - The article outlines six key challenges that need to be addressed for agents to transition from proof of concept to production, including security, memory management, and tool discovery [12][13] Group 3: Amazon Bedrock AgentCore - AWS introduced Amazon Bedrock AgentCore to lower the barriers for building enterprise-level agents, providing a comprehensive solution that includes runtime environments, memory systems, and identity management [15][19] - The AgentCore framework allows developers to deploy agents without needing extensive knowledge of cloud-native environments, thus facilitating faster and safer deployment [15][19] Group 4: Customization and Advanced Features - For enterprises with specific needs, AWS offers advanced features like S3 Vectors for efficient vector storage and retrieval, and Amazon Nova for model customization [21][25] - The introduction of Kiro, an AI IDE product, aims to enhance coding efficiency by integrating product requirements and documentation into the development process [26]

生成式AI 一、 谷歌DeepMind 推 出 新架构MoR实现两倍推理速度 1. MoR架构实现参数共享与自适应计算相结合，以更少参数达到大模型性能； 2. 动态路由机制根据token复杂度分配不同递归深度，减少冗余计算并优化KV缓存； 3. 实验证明MoR推理吞吐量最高提升2.06倍，训练时间减少19%，峰值内存下降25%。 https://mp.weixin.qq.com/s/6IUoCHjm9P_FZllxBlQHPQ 二、 亚马逊推Agent全家桶！5招连发，吹响AI集结号 1. 亚马逊发布Bedrock AgentCore预览版，提供7大AI agents核心服务，包括运行时、记 忆、身份验证等； 2. 推出Nova定制选项和Strands Agents V1.0，使agents开发更简单，实现多agents协同工 作； 四、 谷歌搜索A I将可以 替你电话约服务，还会谈价砍单 1. 谷歌搜索推出AI代打电话功能，可为用户自动联系并预约本地服务，如宠物美容； 2. 搜索集成Gemini 2.5 Pro模型和Deep Search功能，能处理复杂查询并生成深度报告； 3. 发布Amazon S3 V ...