real world autonomous model on pc

Local world brain, dumb but reliable limbs The “intelligence” lives on a small PC in a fire truck, garbage depot, or vehicle—no cloud. Robots/vehicles just execute low-level commands (drive here, grab that, spray now). Unified world model across tasks One model learns a shared representation of: Urban layouts (roads, alleys, building entrances) Dynamic agents (cars, pedestrians, smoke, fire, trash piles, bins) Constraints (no-go zones, safety margins, traffic rules) Same latent space, different “heads” for different tasks: fire support, rubbish routing, autonomous driving. Task heads instead of separate systems Fire Assist Head: Suggests hose positioning, safe approach routes, and “don’t-cross” zones based on smoke, heat, and building geometry. Operates as a co-pilot for firefighters, not a replacement. Rubbish Ops Head: Plans optimal micro-routes for small collection bots in tight alleys and compounds. Learns patterns like “this corner always has overflow after 8pm”. Traffic Head: Handles complex intersections, unprotected turns, and chaotic mixed traffic by predicting short-horizon trajectories of nearby agents.