Heterogeneous Artificial Intelligence

Heterogeneous Artificial Intelligence (HAI) focuses on developing and deploying AI systems composed of diverse components, including different hardware architectures, algorithms, and data sources. Current research emphasizes efficient collaboration among these heterogeneous elements, exploring techniques like federated learning and multi-agent reinforcement learning to optimize performance and energy consumption across varied devices and models. This work is crucial for enabling large-scale AI applications, particularly in resource-constrained environments like the Internet of Things (IoT) and for improving the energy efficiency of computationally intensive AI tasks. The development of open-source toolboxes and benchmarks further facilitates progress and collaboration within the field.