AI 기상 모델은 더 빠르지만, 물리를 대체할 수 있을까?
Google과 NVIDIA의 AI 기상 모델은 기존 방식보다 앞서가지만 예측 가능성과 데이터 의존성 측면에서 엄격한 한계에 직면해 있습니다.
companies like google, nvidia, and microsoft have developed machine learning models for weather forecasting that offer significant speed advantages over traditional numerical methods by skipping complex physics calculations. despite these efficiency gains, the technology faces inherent limitations regarding data quality, generalization to unseen scenarios, and a lack of internal transparency. major weather centers are now exploring hybrid approaches to leverage these speed benefits while mitigating the risks of relying on black-box algorithms.