The article "The Roadmap to 6G – AI Empowered Wireless Networks" by Khaled B. Letaief, Wei Chen, Yuanming Shi, Jun Zhang, and Ying-Jun Angela Zhang discusses the future evolution of wireless communications, focusing on the transformative nature of 6G. 6G is expected to go beyond mobile internet and support ubiquitous AI services, with AI playing a critical role in its design and optimization. The authors outline key trends and requirements for 6G, including very high data rates, up to 1 Tbps, and the introduction of new service types such as Computation Oriented Communications (COC), Contextually Agile eMBB Communications (CAeC), and Event Defined uRLLC (EDuRLLC). They propose a roadmap for 6G, emphasizing the importance of network intelligentization, subnetwork evolution, and intelligent radio. The article also explores AI-enabled technologies for 6G, including big data analytics, closed-loop optimization, and intelligent wireless communication. Additionally, it addresses the challenges and opportunities for 6G in supporting mobile AI applications, such as distributed machine learning and communication-efficient distributed training and inference. The authors conclude by highlighting the need for hardware-aware communications to address the heterogeneity and resource constraints of 6G networks.The article "The Roadmap to 6G – AI Empowered Wireless Networks" by Khaled B. Letaief, Wei Chen, Yuanming Shi, Jun Zhang, and Ying-Jun Angela Zhang discusses the future evolution of wireless communications, focusing on the transformative nature of 6G. 6G is expected to go beyond mobile internet and support ubiquitous AI services, with AI playing a critical role in its design and optimization. The authors outline key trends and requirements for 6G, including very high data rates, up to 1 Tbps, and the introduction of new service types such as Computation Oriented Communications (COC), Contextually Agile eMBB Communications (CAeC), and Event Defined uRLLC (EDuRLLC). They propose a roadmap for 6G, emphasizing the importance of network intelligentization, subnetwork evolution, and intelligent radio. The article also explores AI-enabled technologies for 6G, including big data analytics, closed-loop optimization, and intelligent wireless communication. Additionally, it addresses the challenges and opportunities for 6G in supporting mobile AI applications, such as distributed machine learning and communication-efficient distributed training and inference. The authors conclude by highlighting the need for hardware-aware communications to address the heterogeneity and resource constraints of 6G networks.