Article Best Practices to Build EnergyEfficient AI/ML Systems

News Source : InfoQ.com
News Summary
- AI adoption rate has dramatically increased leading to complex and highly compute intensive AI/ML systems
- Organizations constantly update their ML infrastructures to support model training and deployment
- By striking a balance between performance and energy efficiency throughout the ML process, researchers, and practitioners can contribute to more sustainable innovations in AI
For organizations using AI/ML technologies, it is crucial to systematically track the carbon footprint of ML lifecycle and implement best practices in model development and deployment stages. [+30391 chars]