AI’s new race: cheaper, smarter systems outrun bigger models
The AI race is shifting from chasing the biggest models to building orchestration systems that pick the right model for each task at the right cost, using data and tools as needed. Open-weight models are gaining ground, potentially delivering most tokens in 18–24 months and pressuring the pricing power of dominant labs. This fuels a move toward near-data, task-specific deployments and a hybrid compute approach, while raising strategic concerns about national competitiveness and regulation as Chinese open models grow in importance.
