What techniques enhance the resilience of Generative AI for noisy inputs

Question

Can you tell me What techniques enhance the resilience of Generative AI for noisy inputs?

Answer 1

Techniques enhancing the resilience of Generative AI for noisy inputs include noise-aware training, adversarial augmentation, and denoising autoencoders.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Noise-Aware Training: Exposes the model to noisy data to improve robustness.
• Denoising Autoencoders: Learn to reconstruct clean data from corrupted inputs.
• Adversarial Augmentation: Introduces controlled perturbations to enhance generalization.
• Self-Supervised Learning: Leverages contrastive learning to differentiate signal from noise.

Hence, by referring to above, you can enhance the resilience of Generative AI for noisy inputs