Neural Synthesis in Motion
Exploring the intersection of biological neural networks and algorithmic creativity through dynamic digital art.
Algorithmic Expression
2025This generative artwork uses a 12-layer neural network with adversarial training to create dynamic visual patterns that evolve in real-time. The piece was rendered using 20,000+ epochs of training across 8 Tesla V100 GPUs, with post-processing in Blender and TouchDesigner.
Medium
Digital Neural Network (GAN-based)
Dimensions
4K Ultra HD (3840x2160)
Format
Interactive WebGL Experience
License
Creative Commons BY-SA 4.0
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The Creative Process Behind This Work
Phase 1: Initialization with 100,000 image embeddings from classical artworks
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1
Data preparation with 200,000+ pre-trained convolutional layers and custom normalization matrices for enhanced divergence
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2
Latent space exploration using 512-dimensional vector fields and manifold regularization techniques
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3
Multi-scale discriminator networks with attention-based feature extraction
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4
Post-processing with style transfer filters using 4,096-channel feature maps