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10月4日周日
10月3日周六
  1. OpenAI News

    A model guide for the GPT-6 family

    中文摘要

    了解初创公司如何选择GPT-6模型、调整推理努力程度、改进提示和技能、协调工具,并为生产准备工作流程。

    英文原文

    Learn how startups can choose GPT-6 models, tune reasoning effort, improve prompts and skills, coordinate tools, and prepare workflows for production.

10月2日周五
  1. AWS Machine Learning Blog

    Sweep thousands of leases for compliance using Amazon Quick and the Adjudicated Query pattern

    中文摘要

    已裁定查询模式将Amazon Quick聊天代理与受约束的MCP服务器通过确定性规则引擎配对,以提供可证明完整且有据可依的合规性答案。本文将逐步介绍参考架构和可部署的AWS CDK示例,以租赁合规性为例进行说明。

    英文原文

    The Adjudicated Query pattern pairs the Amazon Quick chat agent with a bounded MCP server over a deterministic rules engine to deliver provably complete, defensible compliance answers. This post walks through the reference architecture and a deployable AWS CDK sample, using lease compliance as the running example.

  2. AWS Machine Learning Blog

    Add secure Web Search to Claude Desktop with Amazon Bedrock AgentCore

    中文摘要

    Amazon Bedrock 上的 Claude Desktop 仅限于该模型的知识截止日期,不支持网络搜索。在本文中,我们将逐步介绍如何使用 Amazon Bedrock AgentCore 网关将 Claude Desktop 连接到网络搜索,通过 AWS IAM Identity Center 和 Amazon Cognito 进行基于 JWT 的入站身份验证。

    英文原文

    Claude Desktop on Amazon Bedrock is limited to the model's knowledge cutoff without web search. In this post, we walk through connecting Claude Desktop to Web Search using Amazon Bedrock AgentCore Gateway, with JWT-based inbound authentication through AWS IAM Identity Center and Amazon Cognito.

  3. AWS Machine Learning Blog

    Fine-tune a search agent with multi-turn RL on Amazon SageMaker AI

    中文摘要

    微调可以教会一个小型搜索代理你的工具和环境,使其在更低的延迟和成本下,具备前沿模型的可靠性。在本文中,我们使用多轮强化学习(MTRL)在Amazon SageMaker AI上对一个由大型语言模型驱动的搜索代理进行微调,并分享我们在检索质量和可靠性方面测量到的提升。

    英文原文

    Fine-tuning teaches a small search agent your tools and environment, giving it the reliability of a frontier model at lower latency and cost. In this post, we fine-tune an LLM-powered search agent with multi-turn reinforcement learning (MTRL) on Amazon SageMaker AI and share the gains we measured in retrieval quality and reliability.

  4. GitHub Blog · AI & ML

    AI is changing developer work. Here are three skills to strengthen.

    中文摘要

    学习如何指导AI代理,批判性地审查它们的输出,并将技术判断置于工作流程的中心。后AI时代正在改变开发人员的工作方式。以下是三项需要加强的技能。首次出现在 The GitHub Blog 上。

    英文原文

    Learn to direct AI agents, critically review their output, and keep technical judgment at the center of your workflow. The post AI is changing developer work. Here are three skills to strengthen. appeared first on The GitHub Blog .

  5. NVIDIA Blog

    NVIDIA DGX Spark 64GB Gives Developers More Ways to Build and Scale Local AI

    中文摘要

    本地人工智能正变得越来越有用。随着AI代理从实验阶段进入日常开发,功能越来越强大的开源模型正在缩小,以适应更多设备,使开发者能够在本地运行更多内容。本月即将推出,NVIDIA DGX Spark将通过顶级制造商合作伙伴——Acer、……提供64GB的统一内存。

    英文原文

    Local AI is becoming more useful by the token. As AI agents move from experiments into everyday development, increasingly capable open models are shrinking to fit on more devices, giving builders more to run locally. Coming this month, NVIDIA DGX Spark will be available with 64GB of unified memory from top manufacturer partners — Acer, […]

  6. OpenAI News

    Chatham scales its capital markets expertise with OpenAI

    中文摘要

    Chatham Financial 使用 Codex 和 GPT-5.6 来构建技术和重新设计工作流程,将交易验证时间从 30 分钟减少到不到 4 分钟。

    英文原文

    Chatham Financial uses Codex and GPT-5.6 to build technology and redesign workflows, cutting trade validation from 30 minutes to under 4.

  7. NVIDIA Blog

    How NVIDIA GPUs Help Accelerate OpenAI’s GPT-6 Astra Ultrafast

    中文摘要

    GPT-6 Astra Ultrafast 现已在 OpenAI API 上推出,并可供符合条件的 ChatGPT Work 和 Codex 用户使用。通过 OpenAI 的模型利用 NVIDIA Blackwell 架构的功能,借助推理优化,Ultrafast 的令牌生成速度比 Astra 标准模式快多达 8 倍。对于开发者来说,[…]

    英文原文

    GPT-6 Astra Ultrafast, running on NVIDIA Blackwell GPUs, is available now in the OpenAI API and to eligible ChatGPT Work and Codex users. Accelerated by inference optimizations through OpenAI’s models that tap into the capabilities of the NVIDIA Blackwell architecture, Ultrafast offers up to 8x faster token generation than the Astra Standard mode. For developers, […]

  8. AWS Machine Learning Blog

    Scaling cloud migrations with agentic AI on Amazon Bedrock AgentCore

    中文摘要

    了解AWS专业服务如何利用基于Amazon Bedrock AgentCore的多智能体框架,实现企业级云迁移的端到端自动化。专门构建的AI智能体负责发现、基础设施即代码生成、组合治理以及迁移后操作,将IaC开发时间从数周缩短至数分钟。

    英文原文

    Learn how AWS Professional Services uses a multi-agent framework built on Amazon Bedrock AgentCore to automate enterprise cloud migrations end to end. Purpose-built AI agents handle discovery, infrastructure as code generation, portfolio governance, and post-migration operations, reducing IaC development time from weeks to minutes.

  9. AWS Machine Learning Blog

    Serve live, governed data in AI-built apps with Amazon Quick

    中文摘要

    在 Amazon Quick 中,使用实时数据的应用程序,AI 构建的应用程序会实时查询您受控的 Quick Sight 数据集,而不是静态的、在构建时拍摄的快照。每次查询都会以查看应用程序的人员身份运行,因此行级和列级的安全性会根据每个读者进行应用。了解如何使用自然语言构建、发布和共享实时数据应用程序。

    英文原文

    With Live Data in Apps in Amazon Quick, AI-built apps query your governed Quick Sight datasets in real time instead of static, build-time snapshots. Each query runs as the person viewing the app, so row-level and column-level security apply per reader. Learn how to build, publish, and share a live-data app using natural language.

  10. AWS Machine Learning Blog

    Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors

    中文摘要

    了解如何在NVIDIA NeMo Agent Toolkit(NAT)中使用Amazon S3向量作为持久化内存层,该工具在Amazon Elastic Kubernetes Service(Amazon EKS)上部署。本文将展示NAT的内存子系统的工作原理,并通过一个多元代理投资研究的用例,说明如何使用Amazon S3向量作为自定义内存提供程序。

    英文原文

    Learn how to use Amazon S3 Vectors as the persistent memory layer within the NVIDIA NeMo Agent Toolkit (NAT), deployed on Amazon Elastic Kubernetes Service (Amazon EKS). This post shows how NAT's memory subsystem works and how to implement Amazon S3 Vectors as a custom memory provider, using a multi-agent investment research use case.

  11. OpenAI News

    The eternal complement

    中文摘要

    先进的人工智能可能对突破性想法背后的常规工作最为重要。了解为什么执行能力可能塑造下一个经济以及进步的速度。

    英文原文

    Advanced AI may matter most for the routine work behind breakthrough ideas. Explore why execution could shape the next economy and the pace of progress.

  12. AWS Machine Learning Blog

    Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS

    中文摘要

    生成式AI使得大规模生产个性化内容变得成本低廉,但你该向每个客户展示哪种变体呢?亚马逊支付(Amazon Payments)在Amazon SageMaker AI上使用了多目标上下文老虎机算法来个性化获取流程,使某一受众的单位数转化率有所提升,并且了解到是内容而非模型成为了限制因素。

    英文原文

    Generative AI makes it cheap to produce personalized content at scale, but which variation do you show each customer? Amazon Payments used a multi-objective contextual bandit on Amazon SageMaker AI to personalize an acquisition funnel, achieving a high single-digit conversion lift for one audience, and learning why content, not the model, was the constraint.

  13. AWS Machine Learning Blog

    Building ambient agents with Amazon Bedrock AgentCore: From event-driven signals to human-in-the-loop workflows

    中文摘要

    环境代理会响应事件,例如 Amazon S3 上传、计划任务或警报,而不是等待聊天提示。本文将介绍如何使用 Amazon Bedrock AgentCore 在 Amazon SQS、AWS Lambda 和 Amazon DynamoDB 上构建与框架无关的环境代理,仅使用一个 ask_human 工具和一个用于人工审核的作业页面。

    英文原文

    Ambient agents respond to events such as an Amazon S3 upload, a schedule, or an alert instead of waiting for a chat prompt. This post walks through building framework-agnostic ambient agents on Amazon Bedrock AgentCore using Amazon SQS, AWS Lambda, and Amazon DynamoDB, with a single ask_human tool and a Jobs page for human-in-the-loop review.

  14. AWS Machine Learning Blog

    Implementing Multi-Environment Access for Claude Platform on AWS

    中文摘要

    了解如何通过单一订阅在AWS上配置对Claude平台的安全、多环境访问:跨账户SigV4用于AWS工作负载,开发人员的工作区作用域API密钥,以及外部环境的OIDC联合,所有操作都在专用AI服务账户中实现工作区级别的隔离。

    英文原文

    Learn how to configure secure, multi-environment access to Claude Platform on AWS from a single subscription: cross-account SigV4 for AWS workloads, workspace-scoped API keys for developers, and OIDC federation for external environments, with workspace-level isolation in a dedicated AI Services account.

  15. AWS Machine Learning Blog

    Simplify dashboard drill-down with the Amazon Quick Sight hierarchy filter

    中文摘要

    Amazon Quick Sight 是一种完全托管的、原生云业务智能(BI)功能,用于构建和发布交互式仪表板。新的层次过滤器使仪表板作者能够在单一紧凑的控件中实现丰富、多级的过滤功能,减少杂乱,并在更少的步骤中引导读者找到所需的数据。

    英文原文

    Amazon Quick Sight is a fully managed, cloud-native business intelligence (BI) capability for building and publishing interactive dashboards. The new hierarchy filter gives dashboard authors rich, multi-level filtering in a single compact control, reducing clutter and guiding readers to the data they need in fewer steps.