[gchadwick]

Whilst it's maybe not worth studying them in detail I'd say being aware of their existence and roughly how they work is still useful. Seeing the many varied ways people have done things with neural networks can be useful inspiration for your own ideas and perhaps the ideas and techniques behind GANs will find a new life or a new purpose.

Yes you can just concentrate on the latest models but if you want a better grounding in the field some understanding of the past is important. In particular reusing ideas from the past in a new way and/or with better software/hardware/datasets is a common source of new developments!