What is adversarial training in AI?

What is adversarial training in AI?

Adversarial training is a technique used to improve the robustness of AI models by exposing them to adversarial examples during training.

How does it work in practice?

In practice, adversarial training involves generating slightly modified inputs that can fool the model and including these in the training dataset.

What are the benefits of using adversarial training?

The main benefits include increased model robustness, improved generalization, and better performance in real-world scenarios.

Are there any downsides to this approach?

Yes, it can lead to longer training times and may not always guarantee improved performance on all types of data.