Interesting edge-AI development from Tether/QVAC. They’re pushing a cross-platform framework for BitNet-based LoRA fine-tuning and inference on local hardware, including smartphones and consumer GPUs, instead of relying on the usual CUDA/cloud setup. What caught my attention is not the branding, but the direction: local model customization lower memory footprint with 1-bit architecture broader hardware support across consumer devices less dependence on centralized AI infrastructure If this approach matures, it could matter a lot for private, on-device AI and mobile-first deployment. I wrote a breakdown here: https://btcusa.com/tethers-qvac-fabric-brings-1-bit-llm-fine-tuning-to-smartphones-and-consumer-gpus/ submitted by /u/Enough_Angle_7839
Originally posted by u/Enough_Angle_7839 on r/ArtificialInteligence