Specific AI Deepenings
Applying AI methods to fresh problems often requires new methods and strategies. Spatially ordered data, for example, can usually be better processed with CNNs (Convolutional Neural Networks), time series with RNNs (Recurrent neural networks), and speech data, for which longer temporal relationships need to be accounted, via so-called transformers. Depending on the availability and quality of the data sets and annotations, unsupervised and self-supervised learning strategies as well as a wide variety of data augmentation techniques are in employ. A basic understanding of these architectures, learning strategies and other AI methods enables efficient solutions to be found quickly.