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

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