However, multimodal AI training also presents some challenges, such as:
- Data integration: combining data from different modalities can be complex and require significant data preprocessing and cleaning
- Model complexity: multimodal models can be more complex and require more computational resources than unimodal models
- Training data quality: the quality of the training data can have a significant impact on the performance of multimodal models