Settings Zero-Training AI™ Demos

My name is William Sergio and this website features some of the breakthroughs in Artificial Intelligence I developed. My work in AI has been featured in more than 100 publication including in a full-page in People Magazine. I am listed in Marquis Who’s Who in America and Who’s Who in Advertising. Many years ago developed a new form of AI that I call Zero-Training AI™, a physics-inspired revolutionary AI framework that maps decisions across a constrained state space. Using defined variables, objectives, boundary conditions, and optimization surfaces, it derives BEST decisions without any training datasets.
All examples are original and engineered to showcase real-world applications of Zero-Training AI™ that requires NO data and NO training to deliver real-time judgment, compounding decisions, and mathematically stable outputs.

Settings Rubik's Cube Solver

Automatically analyze every possible Rubik’s Cube move and select the best sequence to transform a scrambled cube into six perfectly matched faces. This is Real Zero-Training AI™ solving a real problem!

Try Rubik's Cube Solver
Settings Let's Go To Mars!

A spacecraft departs Earth for Mars under real constraints. Adjust thrust limits, fuel, time-of-flight, gravity strength, perturbations, and goal tolerance and watch trajectory re-compute instantly.

Let's Go to Mars
Settings Budget Allocator

Automatically allocate a starting budget across hundreds of meda buys for Half Hours of television time for infomercials to maximize overall NET PROFIT. This is Real Media Buying that makes serious money!

Try Budget Allocator
Settings Drone Hover Stabilizer

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.

Try Drone Hover
CS2 Flipper Market Allocator

Paste a list of 2 items + prices + fees. Zero-Training AI™ outputs a buy/hold/sell allocation under hard constraints: budget, max-per-item exposure, minimum liquidity, and fee-adjusted profit targets.

Try Flipper Allocator
Settings LLM Hallucination Eliminator

User types a prompt. Model outputs 5 candidate sentences. Zero-Training AI™ filters them and highlights the “safe, consistent, non-hallucinated” one.

Try LLM Token Governor
Settings 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.

Try Robot Arm Balancer