Joing all GPUs to train a community model

The article discusses the potential of pooling GPUs for training a large community model, highlighting the significant collective VRAM available. It raises questions about existing distributed volunteer computing projects and mentions challenges such as latency, weight poisoning, and node reliability. This exploration is relevant for practitioners interested in collaborative model training and understanding the feasibility and limitations of distributed training approaches in AI.