We're continuing our discussion on generative adversarial networks, or "GANs" for short. GANs are like a magical dance between two networks – a generator and a discriminator – creating images from random noise.

Johannes explains that while GANs may seem like magic, they're a powerful tool for generating realistic images from scratch.

We discuss how GANs can be used for generating realistic faces for applications like avatars in web development. Johannes also shares insights into comparing images and content using GANs, which can lead to exciting possibilities like style transfer and image manipulation.

But the magic doesn't stop there! We explore the world of neural radiance fields (NeRFs) and how they enable us to generate new perspectives from single images. Imagine being able to see what an object looks like from different angles with just one photo – it's like a superpower for augmented reality and more.

As Johannes points out, NeRFs are fantastic for compressing information and synthesizing depth and geometry. We discuss potential applications in fields like AR, 3D modeling, and even 3D printing.