For my final project I chose to think about what clergy, holy people, and the like do in their spare time. WATCH TV! Would our robot overloads do the same thing?
For my final project I chose to think about what clergy, holy people, and the like do in their spare time. WATCH TV! Would our robot overloads do the same thing? I venture to guess the would. But what would it look like? Hopefully the end result of this project will represents what the AI might see in it’s mind eye, kind of parallel to how we process and establish neural connections during our sleep – dreams.
I used a base google colab notebook, VisionaryArtGenerator, altered it and then generated 7000 images from the input. Using those images as a dataset, I used a style GAN to create a .pkl file to input into another google colab notebook called Lucid Sonic Dreams.
VisionaryArtGenerator-https://colab.research.google.com/drive/1Zny3nZwzkGqzVd-PBQaEK48w9HC2SaL_?usp=sharing
Original .pkl to start the process-https://drive.google.com/file/d/1Vsx7oGYhGchjHyOs2UOzofaNNULsc3yJ/view?usp=sharing
https://colab.research.google.com/drive/1T6D9Dkjak19tiynIEBIIk4ozZbJd1yFN?usp=sharing
https://colab.research.google.com/drive/1T6D9Dkjak19tiynIEBIIk4ozZbJd1yFN?usp=sharing
Sample of dataset.
Audio source files.
I trained the dataset on two different models, this the start of the landscape model.
This is the output of the model trained with the dataset.
This time I trained the model on birds.
Output form the birds model.
LandscapeToGod process video
LandscapeToGod latent space walk.
BirdToGod process video.
BirdToGod latent space walk.
