Rad Labs

n-dimensional systems / applied proofs

Gradient descent for practical machinery.

Let epsilon drift toward zero while the interface stays legible. Rad Labs studies tiny operators, constraint surfaces, and software that feels inevitable after the first click.

f(x) = argmin Σ loss(model, data) + λ · complexity