Generative AI at the Edge: Design, Deploy, and Optimize Generative AI Models
1h 4mIntermediate2025-01-27
Authors
Kesha Williams
Software Engineering Manager, Speaker, Tech Blogger
Karl Obinna Amalu
Course details
In this course, tech leaders Karl Obinna Amalu and Kesha Williams present a hands-on learning experience, exploring the integration of Generative AI (GenAI) with edge computing using the Google Distributed Edge platform. Learn how to design, develop, deploy, and optimize AI models on edge devices, ensuring low latency and efficient performance, and discover opportunities to practice what you learn. Dive into model compatibility, deployment strategies, performance optimization, and ongoing management of edge AI deployments. Plus, gain insights into the broader landscape of edge computing and its applications. By the end of the course, you will have the skills to implement effective edge AI solutions in real-world scenarios.
Learning objectives
Design and develop Generative AI models optimized for edge deployment, ensuring compatibility with edge devices.
Deploy and manage GenAI models on the Google Distributed Edge platform, using effective deployment strategies and techniques.
Apply performance optimization techniques to improve the efficiency and responsiveness of edge-deployed AI models.
Monitor and maintain edge AI deployments, utilizing tools and methods to ensure ongoing performance and reliability.
Understand the broader scope of edge computing, including its evolution and potential applications across various domains.
Learning objectives
Design and develop Generative AI models optimized for edge deployment, ensuring compatibility with edge devices.
Deploy and manage GenAI models on the Google Distributed Edge platform, using effective deployment strategies and techniques.
Apply performance optimization techniques to improve the efficiency and responsiveness of edge-deployed AI models.
Monitor and maintain edge AI deployments, utilizing tools and methods to ensure ongoing performance and reliability.
Understand the broader scope of edge computing, including its evolution and potential applications across various domains.
Skills covered
Artificial Intelligence for DesignAI Productivity ToolsVideoPhotographyGraphic DesignAnimation and IllustrationBusiness Software and ToolsDeep Dive (X:Y)
Concepts
0. Introduction
- 01 - Welcome to Edge GenAI
- 02 - Review the Edge GenAI project
1. Understanding Edge GenAI
- 03 - Understand edge computing
- 04 - Explore the spectrum of edge computing
- 05 - Examine generative AI
- 06 - Evaluate the intersection of edge and GenAI
2. Exploring Google Distributed Cloud Connected Platform
- 07 - Introducing Google Distributed Cloud (GDC) connected
- 08 - Navigate the Google Distributed Cloud console
- 09 - Set up your self-hosted environment
- 10 - Challenge - Set up your self-hosted development environment
- 11 - Solution - Set up your self-hosted development environment
3. Developing GenAI Models for the Edge
- 12 - Explore common keywords and techniques
- 13 - Enable AI capabilities on GDC connected
- 14 - Navigate Vertex AI on GDC connected
- 15 - Design GenAI models for edge devices
- 16 - Use GenAI models
- 17 - Challenge - Use a GenAI model in Ollama
- 18 - Solution - Use a GenAI model in Ollama
4. Deploying and Managing GenAI Models
- 19 - Prepare and design deployment strategies
- 20 - Deploy GenAI models on self-hosted platforms
- 21 - Challenge - Deploy a GenAI model
- 22 - Solution - Deploy a GenAI model
5. Optimizing and Managing Edge GenAI Applications
- 23 - Optimize, monitor, and maintain edge deployments
- 24 - Implement CI CD for GenAI deployments
- 25 - Secure your GenAI deployments
Conclusion
- 26 - Predicting future trends in Edge GenAI
- 27 - Your Edge GenAI journey