Exploring the growing energy demands of AI systems and the imperative to develop sustainable solutions for the technology's future.

Examining the current landscape of AI energy consumption and investigating pathways toward more efficient systems.

Analyzing the roles and responsibilities of different stakeholders in addressing AI's growing energy consumption challenges.

Exploring innovations in AI algorithms, model optimization, and software frameworks to reduce energy consumption during training and inference.

Exploring cutting-edge hardware innovations like neuromorphic computing, photonic processing, and memory-centric architectures for sustainable AI.