It’s possible, but not certain. Current AI (like large language models) has shown incredible progress, yet it still relies heavily on scale—more data, more compute. That approach may eventually plateau if models stop gaining meaningful capabilities from just being bigger. Breakthroughs in reasoning, efficiency, and real-world understanding might require new architectures or hybrid methods that combine symbolic reasoning, memory, or other innovations. So while today’s approach can go further, it likely isn’t the final destination.