Part 4/13:
The model features a frozen universal backbone with 7 billion parameters, meaning it doesn't require retraining for each new task—just small "adapters" are added. This architecture keeps computational costs low while maintaining state-of-the-art accuracy across applications like infrastructure inspection, environmental monitoring, and wildlife tracking.