Helena Sarin: Why Bigger Isn’t Always Better With GANs And AI Art
The model is then trained till the full collapse.
I store and monitor the generated samples per predefined timeout, stopping the training and decreasing the timeout when I start observing the interesting images.
Generate images and select a couple hundred of those with some potential.
I also generate a bunch of mosaics from these images using Python scripts.
This process, as often with concept art in general, carries a risk of getting a bit too mechanical - the images might lose novelty and become boring so it should be applied judiciously and curated ruthlessly.
Hun mener, at hun på et tidspunkt må opgive at bruge kunstig teknologi i sin kreative proces:
Even with the limitations imposed by not having a lot of compute and huge data sets, GAN is a great medium to explore precisely because the generative models are still imperfect and surprising when used under these constraints. Once their output becomes as predictable as the Instagram filters and BigGAN comes pre-built in Photoshop, it would be a good time to switch to a new medium.