AWS 部落格

生成式 AI
Amazon Bedrock 現已推出 Mistral Large

使用 Amazon Bedrock 上的 Mistral Large 解決複雜的推理任務

Mistral Large 非常適合需要大量推理能力的複雜工作,或高度專業的工作,例如合成文字產生或程式碼產生。 

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成本優化
成本節省特色張貼影像

報告:公司從內部部署遷移至雲端後,AWS 可大幅節省成本

Snap 和 Formula 1 是兩家透過遷移至 AWS 雲端獲益的公司。了解他們為什麼進行轉換,以及如何節省成本。

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資料和分析
資料湖與資料網格部落格特色影像

資料湖與資料網格:導覽組織資料策略的未來

了解資料網格策略如何推動更加分散式、以人為中心和內容特定資料管理方法,藉此克服集中式資料湖的某些限制。

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  • Jason Hunter, 2025年2月11日
    In this post we demonstrate how to enforce client-side timestamp-based write sequence order on Amazon DynamoDB. The goal is to ensure items with lower timestamps don’t overwrite items with higher timestamps, even if the requests are received out of order by the database.
  • Marco Punio, Baladithya Balamurugan, Banu Nagasundaram, Deepak Rupakula, Harish Rao, Naman Nandan, 2025年2月11日
    We are excited to announce that Meta’s Segment Anything Model (SAM) 2.1 vision segmentation model is publicly available through Amazon SageMaker JumpStart to deploy and run inference. Meta SAM 2.1 provides state-of-the-art video and image segmentation capabilities in a single model. In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and deploy a wide range of pre-trained FMs for inference, including Meta’s most advanced and capable models to date.
  • Niithiyn Vijeaswaran, Banu Nagasundaram, Marc Karp, Raghu Ramesha, 2025年2月11日
    We are excited to announce that the Falcon 3 family of models from TII are available in Amazon SageMaker JumpStart. In this post, we explore how to deploy this model efficiently on Amazon SageMaker AI.
  • Andy Rivers, Ves Sathya, 2025年2月11日
    This post is part three of a four-part series that addresses how a Cloud Center of Excellence (CCoE) can be a viable solution to address the challenges of digital transformation. In this post, we address the three technical perspectives of the Amazon Web Services Cloud Adoption Framework (AWS CAF). While the business, organizational, and governance perspectives of the AWS CAF are crucial, the CCoE must also focus on the technical capabilities required to build and operate a cloud environment that meets the organization’s needs.
  • Salman Ahmed, Ankush Goyal, Sergio Barraza, Ravi Kumar, 2025年2月11日
    In this post, we present a streamlined approach to deploying an AI-powered agent by combining Amazon Bedrock Agents and a foundation model (FM). We guide you through the process of configuring the agent and implementing the specific logic required for the virtual meteorologist to provide accurate weather-related responses.
  • Norm Johanson, 2025年2月11日
    .NET Aspire is a new way of building cloud-ready applications. In particular, it provides an orchestration for local environments in which to run, connect, and debug the components of distributed applications. Those components can be .NET projects, databases, containers, or executables. .NET Aspire is designed to have integrations with common components used in distributed applications. [...]
  • Alexandre Alves, 2025年2月11日
    Generative AI is becoming a central component of success in nearly every industry. We have the unique opportunity to see how different businesses within Amazon are using generative AI to create transformative customer experiences—with nearly 1,000 generative AI applications in motion inside Amazon. This blog post is the first in a series that will explore [...]
  • Albeda Siddique, Juan Carlos Sanchez, Nayef Khan, 2025年2月11日
    CSPs face offer personalization challenges due to complex portfolios. Hansen’s AI-driven Offer Lifecycle Management solution, developed in the 2024 TM Forum Catalyst, empowers CSPs to analyze offers, rationalize catalogs, and enhance their OLM process using LLMs and Amazon Bedrock.
  • Jussi Railakari, Anton Garvanko, Roy Yung, 2025年2月11日
    In this post, we share how Wisso replaced an embedded reporting system in their client’s kitchen management application using QuickSight. With QuickSight, the client increased user adoption, saved on costs, and could implement new dashboards faster.
  • Jonathan Jenkyn, Michael Tschannen, 2025年2月11日
    Generative AI applications often involve a combination of various services and features—such as Amazon Bedrock and large language models (LLMs)—to generate content and to access potentially confidential data. This combination requires strong identity and access management controls and is special in the sense that those controls need to be applied on various levels. In this [...]

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