🧪 AI Perfect Simulation
Evolve a population of AI model configurations with a real genetic algorithm and watch trade-offs between accuracy, speed and robustness carve out a Pareto frontier — a working demonstration of why no single 'perfect' AI can dominate every objective at once.
"The perfect AI" sounds like an optimization target — but as soon as an AI has to be accurate, fast, and robust at the same time, there is no single point that maximizes all three. This simulator evolves a population of AI model configurations with a real genetic algorithm (tournament selection, blend crossover, Gaussian mutation, elitism), plots them live in a 3D objective space, and separates the population into a gold Pareto frontier — configurations no other configuration strictly beats — and the dominated majority around it. Three weight sliders crown a single "best" model for a chosen set of priorities, and moving them slides the winner to a different point on the very same frontier, making the trade-off tangible: peak performance is achievable, but "perfect" always depends on what you were optimizing for.
This simulation investigates the creation of an ideal or perfect artificial intelligence. It likely focuses on optimization and achieving peak performance within a defined environment, demonstrating concepts related to algorithmic efficiency.
2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install