Technical background in VLMs and foundation models (worked at Siemens on time series prediction). Co-founded General Instinct to build infrastructure for running physical AI models (world action models, VLAs) fast on edge devices.
no scored calls yet — needs a stated position or a categorical verdict, with a matured window vs SPY
Bill and Guanming argue world action models (WAMs) are too slow and expensive for robotics (2GB, 200s, $70K) and have built infrastructure optimizing diffusion transformers, VAEs, and flow matching to achieve real-time edge deployment.
Nvidia's Dream Zero world action model requires 2GB VRAM and 200 seconds per inference step at ~$70K per unit, making it economically non-scalable for robotics deployment despite strong benchmark performance.