Tag: SageMaker AI
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Amazon SageMaker JumpStart, Foundation Models and Private Hubs (AWS Gen AI Series, Part 18)
SageMaker JumpStart gives you open-weight and proprietary foundation models on your own SageMaker endpoint. Here is how it differs from Bedrock, what it costs, and when the instance bill is worth it.
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Amazon Bedrock vs SageMaker AI, and When to Use Each (AWS Gen AI Series, Part 5)
Bedrock gives you models behind an API; SageMaker AI gives you the whole ML platform. Here is how I decide between them, with the cost math that usually settles it.
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AWS Generative AI Stack, End to End (AWS Gen AI Series, Part 1)
AWS generative AI is really three layers: Amazon Bedrock for managed models, SageMaker AI to build your own, and Trainium and Inferentia underneath. Here is the whole map, with a real cost example and a first call that works.
Architect’s Toolkit
PJ’s Tools
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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