We don't train on the internet. We train on reality.
While others bet on bigger datasets, Mateza builds agents that learn from scratch.
Today's "AI" models—GPT, Claude, Llama—are miracles of engineering, but they are fundamentally Statistical Engines.
They work by compressing the entire internet into a neural network. When you ask them a question, they aren't "thinking"; they are predicting the next most likely word based on the billions of books they have read.
We are hitting the Data Wall. To make current models 10% smarter, we need 100x more data.
But here is the problem: We have already read the internet.
Tech giants are spending billions on bigger GPUs to squeeze marginal gains out of a stagnant pool of data. This is a dead end. You cannot build a superhuman intelligence by only reading human text.
If we cannot read more books, we must experience the world.
Mateza is building the Gymnasium for Minds. We are creating high-fidelity, physics-compliant simulations where our agents live, experiment, and learn.
By solving puzzles in these "Synthetic Realities", our agents derive the laws of logic from scratch. They don't memorize; they understand. This creates a Logic Kernel that is small, efficient, and infinitely scalable.
Agents learn gravity, friction, and causality by interacting with the world.
Self-improving logic structures that build upon previous knowledge.
Intelligence scales with compute, not data. O(N) complexity.
Logic chains are fully auditable, eliminating black-box hallucinations.