When should I use complex models in AI?

When should I consider using complex models in AI?

You should consider using complex models when your data is large and intricate, and simpler models can't capture the patterns.

What types of problems are best suited for complex models?

Complex models are ideal for tasks like image recognition, natural language processing, and any problem with high-dimensional data.

Are there any downsides to using complex models?

Yes, complex models can be prone to overfitting, require more computational resources, and can be harder to interpret.

How do I know if a model is too complex for my data?

You can evaluate model performance using validation techniques; if the model performs significantly better on training data than on validation data, it may be too complex.