COLLECTION 04 / AERIGRID ACADEMY
Sustainable AI Technology
Explore technical approaches to reducing the resource requirements of AI systems.
10 lessons · Learn in any order
The Energy Cost of Machine Learning
Introduce the relationship between computation and electricity consumption.
AI Training vs. AI Inference
Compare the computational and operational characteristics of training and inference.
Measuring AI Energy Efficiency
Explore performance-per-watt, benchmarking, and measurement boundaries.
Efficient AI Chips and Accelerators
Investigate specialized hardware and energy efficiency.
The Environmental Footprint of Semiconductor Manufacturing
Explore material use, electricity demand, water requirements, and embodied impacts.
Smaller Models and Efficient AI Architectures
Introduce model compression, distillation, quantization, and efficiency tradeoffs.
Workload Scheduling and Energy-Aware Computing
Explore how computation scheduling may respond to system conditions.
Liquid Cooling and Waste Heat Reuse
Examine thermal management and practical limitations of heat recovery.
Water-Efficient Computing Infrastructure
Explore water-use metrics, cooling choices, and regional constraints.
Transparent and Reproducible Sustainable AI Research
Explore measurement standards, reporting transparency, and scientific reproducibility.