And the claims that this is good privacy/security are not at all obvious either. And who are those third-parties anyway? Did you verify each one of them?

A neural network, conversely, is a big ball of mud. Impossible to reason about and to test except for whole-system, end-to-end testing, which is impossible to do exhaustively because of the size of the state space. It is, by design, unexplainable and untestable, and therefore unreliable. It's why you use globals in C only judiciously. (I am just rephrasing the article here, not saying anything new.)

And the evidence that it causes practical problems to usefulness is already out there; "hallucinations" are simply errors, just that corporate PR likes to pretend that it's a "feature" and not a bug. This is delusional. A society seeking digitalization should run away from this level of stupidity.

My boy. More people need common sense like this talked into them.

Humanity racing towards maximum idiocy.

Specifically this one, which seems to tackle what you mentioned: https://research.nvidia.com/labs/rtr/publication/hadadan2023...

> // No idea where negative values come from :(

I don't know, but:

> newRay.origin += sign(dot(newRay.direction, geometryNormal)) * geometryNormal * 1e-4;

The new origin should be along the reflected ray, not along the direction of the normal. This line basically adds the normal (with a sign) to the origin (intersection point), which seems odd.

Poor's man way to find where the negatives come from is to max(0,...) stuff until you find it.