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1、Table of ContentsTable of Contents2Introduction4Critical Considerations for Businesses5Scalability5Flexibility5Cost Management5Compliance and Security6Key Components of AI Infrastructure6Data&Storage6Data Management6Data Sources6Data Preparation7Data Ingestion7RAG/Vector Databases7Data Governance8Da

2、ta Monitoring and Observability8Visualization and Analytics8Model Development&Training8Development Environment9Experiment Management9Orchestration9Model Testing and Fine-tuning10Deployment10Models10ML Models10LLMs10Multi-modal Models11Computer Vision Models11Model Hub11Monitoring&Observability11Obse

3、rvability12Monitoring12Model Endpoint Monitoring12Security&Compliance12RBAC13Compute13Hardware13Copyright 2024 by ClearML.All rights reserved.All trademarks are the property of their respective owners.2Compute Options13Cluster Management14Resource Management14Multi-tenancy15Billing15Interoperability

4、15Base AI Frameworks16AI Inference Frameworks16ONNX(Open Neural Network Exchange)16Llama.cpp17vLLM17Triton17Introducing ClearML19How to Evaluate AI Infrastructure Solutions22Checklist for Evaluating AI Infrastructure Solutions23Summary and Next Steps24Next Steps24About ClearML24Copyright 2024 by Cle

5、arML.All rights reserved.All trademarks are the property of their respective owners.3IntroductionWe all know that AI has experienced explosive growth recently,driven by advancements in computing power,algorithms,and the vast amounts of data available.In turn,this growth has driven the need for sophi

6、sticated AIinfrastructure to support the building,training,deployment,and management of AI models as well as GenAIadoption at scale.According to research published by Allied Market Research and reported by CIO News,the trajectory of the GlobalAI Infrastructure Market reflects this burgeoning demand.