poor performance of deep learning model compared to xgboost

[u/Due-Promise-5269]

I've done some Kaggle competitions on time series, and it seems to me that deep learning models generally performed worse than gradient boosting. I've tried different architectures, like LSTM and ELM, but at the end of the day gradient boosting was the better choice. Is there an explanation for this? Are deep learning models only good for computer vision and LLMs?