Energy Efficiency

Energy efficiency research focuses on minimizing energy consumption across diverse applications while maintaining performance. Current efforts concentrate on optimizing model architectures (e.g., spiking neural networks, convolutional neural networks, large language models) and algorithms (e.g., reinforcement learning, self-supervised contrastive learning) to improve efficiency in areas like building management, robotics, and deep learning. These advancements are crucial for mitigating climate change, reducing operational costs, and enabling sustainable deployment of computationally intensive technologies in resource-constrained environments. The field is actively exploring trade-offs between energy consumption, latency, and accuracy to identify Pareto-optimal solutions.