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Course Outline
Introduction to Energy-Efficient AI for Government
- The importance of sustainability in artificial intelligence for government operations
- Overview of energy consumption in machine learning processes for government applications
- Case studies of energy-efficient AI implementations within public sector environments
Compact Model Architectures for Government
- Understanding model size and complexity in the context of government systems
- Techniques for designing small yet effective models for government use
- Comparing different model architectures to optimize efficiency for government tasks
Optimization and Compression Techniques for Government
- Model pruning and quantization methods tailored for government applications
- Knowledge distillation techniques to create smaller models suitable for government needs
- Efficient training methods to reduce energy usage in government AI systems
Hardware Considerations for Government AI
- Selecting energy-efficient hardware for training and inference in government settings
- The role of specialized processors like TPUs and FPGAs in government applications
- Balancing performance and power consumption in government AI infrastructure
Green Coding Practices for Government
- Writing energy-efficient code for government AI systems
- Profiling and optimizing AI algorithms to enhance sustainability in government operations
- Best practices for sustainable software development within the public sector
Renewable Energy and Government AI
- Integrating renewable energy sources into government AI operations
- Data center sustainability initiatives in the public sector
- The future of green AI infrastructure for government agencies
Lifecycle Assessment of Government AI Systems
- Measuring the carbon footprint of AI models used by government entities
- Strategies for reducing environmental impact throughout the AI lifecycle in government operations
- Case studies on lifecycle assessment in government AI projects
Policy and Regulation for Sustainable Government AI
- Understanding global standards and regulations relevant to government AI
- The role of policy in promoting energy-efficient AI within the public sector
- Ethical considerations and societal impact of government AI initiatives
Project and Assessment for Government
- Developing a prototype using small language models in a chosen domain for government use
- Presentation of the energy-efficient AI system designed for government applications
- Evaluation based on technical efficiency, innovation, and environmental contribution to government operations
Summary and Next Steps for Government
Requirements
- A strong grasp of deep learning principles
- Expertise in Python programming
- Experience with model optimization methods
Audience
- Machine learning engineers for government and private sectors
- AI researchers and practitioners
- Environmental advocates within the technology industry
21 Hours