What are the differences between hybrid and pure AI models?

What are the differences between hybrid and pure AI models?

Hybrid AI models combine both rule-based and machine learning approaches, while pure AI models rely solely on one of these methods.

Can you give examples of each type?

Sure! An example of a hybrid model is IBM's Watson, which uses both machine learning and expert systems. A pure AI model could be a neural network used for image recognition.

What are the advantages of using hybrid models?

Hybrid models can leverage the strengths of both approaches, providing better accuracy and flexibility in various applications.

Are there any disadvantages to hybrid models?

Yes, hybrid models can be more complex to develop and maintain, and they may require more computational resources.

Which model is better for real-time applications?

It often depends on the specific use case, but hybrid models can be more effective in real-time applications due to their adaptability.