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借助 Amazon SageMaker AI 简化 AI 模型开发生命周期.pdf

上传人: 明**** 编号:1012713 2025-12-21 39页 985.13KB

1、A I M 3 6 4Streamline AI model development lifecycle with Amazon SageMaker AIKhushboo SrivastavaSr.Product Manager TechnicalAmazon Web ServicesBruno PistoneSr.WW Specialist SAGenAIAmazon Web ServicesManikandan ParamasivanSenior Staff Architect-Data,ML&AIKOHO 2025,Amazon Web Services,Inc.or its affil

2、iates.All rights reserved.$202BGenAI spending by 20281$7TIncrease in global GDP(7%)2STATE OF GENERATIVE AI IN THE ENTERPRISES32%overall AI spending29%CAGRProductivity increases 1.5 percentage points over next 10 years1.IDC 2.Goldman Sachs 2025,Amazon Web Services,Inc.or its affiliates.All rights res

3、erved.of enterprises are actively advancing their generative AI initiatives in 2025,with 92%planning to increase investment by 2027https:/aloa.co/ai/resources/industry-insights/ai-statsof organizations choose AI models that are 13B parameters or smaller,suggesting preference for customizable,cost-ef

4、fective models rather than larger generic oneshttps:/ organizations now use AI in at least one business functionhttps:/ AI adoption momentum is real 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Disparate and disconnected ML tools increases time to marketIsolation between team m

5、embers reduces productivity and collaborationChallenging to govern AI and ML projects efficientlyTraining infrastructure provision and management To build,train,and deploy AI models at scale is challenging 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.C L A S S I C M LG E N A ID

6、ata prepPrepare data assets and pipelines,manage data quality and biasBuildExperiment and automate the execution of build pipelinesTrainTrain ML models at scale with automation DeployAutomate the execution of deploy pipelines into productionA U T O M A T E W I T H A I O P S A N D G O V E R N A N C E

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根据报告的内容,全文主要内容概括如下: - **AI市场增长**:预计到2027年,企业对生成式AI的投资将增长,全球GDP增长7%,AI支出增长32%,年复合增长率29%。 - **AI模型选择**:多数组织选择参数小于13B的AI模型,偏好定制化、成本效益高的模型。 - **AI应用现状**:89%的组织在至少一个业务功能中使用AI,78%的企业正在积极推动AI项目。 - **AI挑战**:数据准备、模型训练、部署和治理是AI项目的主要挑战。 - **Amazon SageMaker**:提供端到端AI和ML模型生命周期工具,包括数据准备、训练、部署和监控。 - **SageMaker Studio**:集成AI开发工具,简化AI模型开发流程。 - **SageMaker HyperPod**:提供弹性、自管理的训练和推理基础设施。 - **案例研究**:KOHO银行使用SageMaker Studio实现98%的成本降低,并提高了性能和准确性。
"AI模型开发,SageMaker如何简化?" "企业AI投资,2027年将增多少?" "SageMaker Studio,ML全流程工具!"
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