One of the primary challenges associated with artificial intelligence (AI) is that models can be brittle, meaning small changes to either the input data or the model itself can cause the AI to fail or produce inaccurate results. Because it can be difficult to replicate training conditions in the real world, and because it may…
Tag: robustness
Neural networks that are sensitive to small changes in the data
There are many ways to make neural networks more robust to small changes in data and architecture. One way is to use data augmentation, which essentially creates more data by artificially changing the data that already exists. This can be done by adding noise, flipping images, or other types of transformations. Data augmentation can help…