Editing Openai/6945f9bd-f198-8008-bb8c-1ab730279e5f (section)

==== ### ====

GPUs currently understand:
* Zero
* Masked execution

They do not understand:
* Non-existence as a first-class concept

Null space must be:
* Declared
* Propagated
* Eliminated before kernel execution

This is essential to avoid wasted computation.

===== Branching is poison for GPUs. =====

nDspace eliminates branching conceptually—but only if:
* Conditional logic is lifted into dimensions
* Invocation is resolved before execution
* Projection is the only runtime operation

This requires early binding of applicability, which many programmers are not trained to do.

===== How do you store: =====
* Sparse high-dimensional state
* With variable active dimensions
* And fast projection paths

Options:
* Sparse tensors
* Factorized representations
* Constraint-indexed buffers

Each comes with trade-offs in:
* Memory locality
* Cache coherence
* Update cost

This is where most naive designs fail.

===== This is underestimated but real. =====

Programmers are trained to think in:
* Loops
* Conditionals
* State mutation

nDspace demands thinking in:
* Independence
* Constraint
* Projection
* Nullity

NodeBox showed humans can do this visually—but formalizing it is a cultural shift.