initially these images are very hazy fuzzy it you know you can't really see what's going on right now but through the power of auto-encoders what happens is that the noise is removed and it's a more crisper image you can see so now a third example is anomaly detection now what anomaly detection is it's basically a technique for identifying patterns within data so patterns that do not follow the norm so for example in autoencoders for example we have this idea of reconstruction errors so if an observation right it's passed in and it