AI Native Wireless Networks Overview - NVIDIA AI Aerial is revolutionizing wireless systems by enabling neural networks to learn from data, adapt in real-time, and scale with complexity [1] - This approach boosts spectral efficiency, lowers costs, and improves connectivity in wireless networks [1] Key Steps & Technologies - Building AI native wireless networks involves three key steps: training, simulation, and deployment, all unified by NVIDIA AI Aerial [2] - NVIDIA uses Shauna and Aerial radio frameworks to train neural network models, replacing traditional 5G channel estimation algorithms [2] - The trained model is deployed on a live 5G network at NVIDIA using Aerial RAN computer [3] - NVIDIA provides the Shona research kit on NVIDIA Jetson, enabling developers to create a working AI model in a live 5G network with minimal code [5] Performance & Results - AI implementation nearly doubles the cell throughput [3] - AI achieves 100% higher throughput on a live 5G network [4] - The AI model continuously improves over time through a feedback loop between the physical and virtual worlds [4] Future Implications - Improved AI models will boost capacity, unlock new applications, increase efficiency, and extend coverage [5] - NVIDIA encourages participation in the 6G developer program to accelerate AI native wireless research [5]