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在工业自动化中实现边缘智能体人工智能.pdf

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1、 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.H M C 3 1 7Implement Agentic AI at the edge for industrial automationMohamed SalahSr Solutions Arc

2、hitectKarim AkhnoukhSr Solutions Architect 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.11%Cost the worlds 500 biggest companies of their revenues due to unplanned downtimeC O S T O F D O W N T I M E$1.4 trillion for Manufacturing equivalent to the annual GDP of a nation likeTh

3、e Cost of Downtime 2024 Report by SIEMENS 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.ChallengesOperational DisruptionsWhen the network drops,the system goes quiet.Skills gapKnowledge is locked in experts heads.Production DelaysToo much data.Too little context.Data SilosDiscon

4、nected systems.Disconnected decisions.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Data SourcesUnified Data FlowTelemetry&AlarmsDocuments&SopsEnvironment&external DataPOST HTTPLoRaWANMQTTsFTPGET HTTPAmazon QuickSightUnified APIAWS CloudAmazon EC2Amazon EKSS3-compatible object s

5、torageAWS OutpostsAmazonBedrock 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Data SourcesAlways ONTelemetry&AlarmsDocuments&SopsEnvironment&external DataPOST HTTPLoRaWANMQTTsFTPGET HTTPAmazon QuickSightAmazonBed

6、rockUnified APIAWS CloudAmazon EC2Amazon EKSAWS OutpostsS3-compatible object storage 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Data SourcesAlways ONTelemetry&AlarmsDocuments&SopsEnvironment&external DataPOST HTTPLoRaWANMQTTsFTPGET HTTPAmazon QuickSightAmazonBedrockUnified AP

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根据《Implement Agentic AI at the Edge for Industrial Automation》报告,以下为全文关键点: 1. **停机成本**:全球500强企业因计划外停机损失达1.4万亿美元,相当于一个国家的年度GDP。 2. **挑战**:运营中断、技能差距、生产延误、数据孤岛。 3. **解决方案**:使用AWS云服务,包括EC2、EKS、S3兼容对象存储、Outposts和Bedrock。 4. **数据源**:统一数据流,包括遥测、警报、文档、SOP、环境数据和外部数据。 5. **边缘智能**:使用NVIDIA T4 GPU加速器,实现高效数据处理和模型推理。 6. **量化策略**:FP16(全精度)和MXFP4量化,实现65%的内存节省和1-2%的精度损失。 7. **吞吐量和成本**:通过模型复制和GPU容量优化,提高吞吐量并降低成本。 8. **数据准备和微调**:快速模型下载和微调,实现智能决策和持续学习。 9. **连接操作**:通过AI驱动的连续学习和智能决策,实现工厂的智能连接操作。
"边缘AI如何助力工业自动化?" "减少停机成本,AI如何行动?" "工业自动化中的数据孤岛,AI如何破局?"
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