Computational Resource

Computational resource management in artificial intelligence is a critical area of research focusing on optimizing the efficiency and sustainability of AI model development and deployment. Current efforts concentrate on developing energy-efficient model architectures like spiking neural networks (SNNs) and smaller, context-specific language models, alongside strategies for efficient training and inference, including techniques like training-free conversion, active learning, and resource-aware scheduling. These advancements are crucial for mitigating the environmental impact of AI and enabling broader access to powerful AI tools, particularly in resource-constrained settings.