더 큰 모델보다 더 나은 데이터가 먼저다

While LLMs and hardware infrastructure have attracted massive investment, high-quality domain-specific data—the actual bottleneck—remains systematically overlooked. AI's performance gaps in complex domains like healthcare and customer support stem not from architectural limitations, but from insufficient curated training data. Bridging this data infrastructure gap through scientific data design is essential for AI's next breakthrough.