Zero-Training AI™ Demos
Budget Allocator
Automatically allocate a starting budget across hundreds of meda buys for Half Hours of television time for infomerrcials to maximize overall NET PROFIT.
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Drone Hover Stabilizer Simulation
A small quad-drone icon tries to remain level. You press buttons like Wind Gust, Tilt, and Disturbance, and the drone re-stabilizes instantly. Visual scaling represents relative control energy, not physical motion.
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Robot Arm Balancer
A simple animated 2-joint “robot arm” tries to hold a target point. When user moves the target, the arm smoothly finds a stable configuration. No “machine learning”—just pure real-time control.
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LLM Token Governor (Hallucination Eliminator)
User types a prompt. Model outputs 5 candidate sentences. Zero-Training AI™ filters them and highlights the “safe, consistent, non-hallucinated” one.
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Zero-Training AI™ demonstrates how deterministic decision systems can operate without training data, datasets, or machine learning models. The systems shown here evaluate candidate actions in real time within a defined Decision Space, producing stable and explainable outcomes across multiple domains.