Tcho

t__cho develops generative art systems, machine learning models, and computational music through a research-driven practice bridging creative code and artificial intelligence. Their technical work spans visual synthesis algorithms, deep learning architectures for audio generation, and experimental approaches to human-AI creative collaboration. The projects integrate philosophical inquiry into technological systems while advancing novel applications of neural networks and procedural techniques. Their public documentation and analysis examines emerging developments in creative AI, sharing technical insights via Bluesky and X platforms alongside working code demonstrations. The content focuses on practical applications of machine learning models, generative methods for audiovisual art, and critical perspectives on computational creativity. Regular updates cover new research findings, project experiments, and evolving frameworks for AI-assisted artistic production. The work situates computational art practice within broader discussions of technological change, creative automation, and digital culture. Technical implementations are accompanied by theoretical context exploring AI's role in creative processes. This research-based approach connects hands-on development with examination of how emerging tools reshape artistic possibilities.