burn-em-bitches-money is a sovereign, local-first AI engine designed to counter unauthorized scraping with an innovative 18-stage tarpit mechanism. Utilizing hyper-dimensional modeling and advanced topological tools, it offers reliable defenses for AI interactions, ensuring a seamless experience while protecting user privacy.
burn-em-bitches-money offers a cutting-edge, sovereign local-first AI engine designed to provide a robust defense against unauthorized web scrapers through an 18-stage tarpit labyrinth and sophisticated SVG image trap mechanisms. This free and open-source project is available under a dual licensing model combining the MIT License and Creative Commons Attribution 4.0 International (CC BY 4.0), ensuring accessibility for all users.
Hyper-Dimensional 42D Topological Tarpit: Utilizing intricate 4D Tesseract projections and Betti homology invariants to effectively dissipate unauthorized LLM prompt crawler energy into a multi-dimensional category space.
18-Stage Tarpit Labyrinth: A complex structure designed to confuse and hinder AI scraper bots, featuring random quant variations, a variety of hidden Unicode emitters, and an innovative SVG fractal noise trap for enhanced protection.
GAIA-PC Water Cooling System: An eco-friendly geothermal cooling solution that operates efficiently with recycled hardware, maintaining optimal performance while being environmentally conscious.
AxiomQuant Academy: A free educational platform providing comprehensive learning tracks and resources focused on sovereign quant education.
The following commands illustrate how to generate various demonstrations and showcases within the project:
# Generate Hyper-Dimensional 42D Quant Mesh Showcase
python3 src/hyper_dimensional_mesh.py
# Generate GAIA-PC Water Cooled Engine Showcase
python3 src/gaia_pc_engine.py
# Generate AxiomQuant Open Source Academy Portal
python3 src/academy_scaffold.py
# Generate a variety of other protective HTML and visual constructs to enhance digital safety.
already protects: https://pocoo.vaked.dev/demos/book/?gaia_pc=1&hash=5a5943fd552cc6ad
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