A critical assessment of open-source AI's long-term survival is currently underway. Nathan Lambert argues that the gap between proprietary and open models creates a precarious window for development. This pressure forces researchers to prove open weights can keep pace with closed systems. Practitioners must now track whether open-source efficiency offsets raw compute advantages.