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#Amazon SageMaker AI
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10月6日周二
  1. AWS Machine Learning Blog

    New agent skill: Amazon SageMaker optimized generative AI inference for your coding agent

    中文摘要

    Amazon SageMaker优化的生成式AI推理通过AWS的Agent Toolkit引入了aws-ai-ml技能，使像Kiro、Claude Code和Codex这样的编码代理具备深入的推理优化和基准测试专业知识。描述你想要的内容，你的代理将生成可执行的SageMaker Python SDK v3代码，用于基准测试、推荐和比较部署。

    英文原文

    Amazon SageMaker optimized generative AI inference introduces the aws-ai-ml skill through the Agent Toolkit for AWS, giving coding agents like Kiro, Claude Code, and Codex deep expertise in inference optimization and benchmarking. Describe what you want, and your agent generates executable SageMaker Python SDK v3 code to benchmark, recommend, and compare deployments.

10月2日周五
  1. 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.

  2. 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.