AI Infrastructures: Memory, Power, and Deployments at the Heart of GTC 2026

AI infrastructures are rapidly evolving, driven by the increasing complexity of models and the need to process vast amounts of data. According to DIGITIMES, three main challenges will dominate the technological landscape at GTC 2026: memory management, energy efficiency, and deployment-related issues.

The demand for memory for AI models, especially for large language models (LLMs), is constantly increasing. This requires the development of new memory architectures and more efficient management techniques. At the same time, energy consumption represents an increasingly stringent constraint, pushing manufacturers to focus on hardware and software solutions that optimize the performance-to-consumption ratio.

Finally, deployment challenges, due to geopolitical factors and the complexity of supply chains, require greater attention to the diversification of sources and the resilience of infrastructures. These three factors will jointly shape the future of AI infrastructures, influencing the development, implementation, and management decisions of artificial intelligence systems.