Building Amazon Nova Foundation Models with SageMaker HyperPod

Overview

Discover how Amazon leverages SageMaker HyperPod's infrastructure and tools to develop Nova Foundation Models, exploring distributed training, observability, and cost-effective inference solutions.

Syllabus

• Introduction to Amazon Nova Foundation Models
Overview of Nova Foundation Models
Significance and applications of foundation models
• Amazon SageMaker HyperPod Overview
Introduction to SageMaker HyperPod
Key features and advantages
Infrastructure components
• Setting Up the SageMaker HyperPod Environment
Prerequisites and resource allocation
Environment configuration and setup
• Developing Nova Foundation Models with SageMaker HyperPod
Model design and architecture
Best practices for leveraging SageMaker tools
• Distributed Training on SageMaker HyperPod
Fundamentals of distributed training
Implementing distributed training with SageMaker
Scaling models efficiently
• Observability in Model Training
Monitoring and logging with SageMaker
Diagnosing and troubleshooting training processes
Tools for improving model training visibility
• Cost-Effective Inference Solutions
Optimizing inference costs with SageMaker
Deploying models for efficient inference
Utilizing SageMaker features for cost management
• Case Studies and Practical Applications
Real-world examples of Nova Foundation Models
Lessons learned from industry use cases
• Conclusion and Future Trends
Key takeaways from building Nova Foundation Models
Emerging trends in AI and large-scale model development

Subjects

Programming