The Center systematically builds hardware/software systems and develops fundamental theories of artificial intelligence, focusing on 11 major areas: Machine Learning Theory, Model Training and Inference Frameworks, Mathematical Mechanisms, Statistical Optimization of Models, Computing Cluster Architectures, Core Operator Development/Cluster Fault Management, Computing Resource Scheduling, Cluster Communication Optimization, AI Chip Design, Next-Generation AI System Architecture Methods and Mixed-Precision Algorithms.

• Machine Learning Theory
• Model Training and Inference Frameworks
• Mathematical Mechanisms of Models
• Statistical Optimization Methods
• Computing Cluster Architectures
• Next-generation AI System Architecture Methods and Mixed-precision Algorithms
• Cluster Fault Management
• Computing Resource Scheduling
• Cluster Communication Optimization
• Operator Development and Optimization
• AI Chip Design