external optimization pipeline
Offline training
Valid claim: Fits parameters before evaluation using the declared data and compute.
Bounded substrate comparison
Offline training and online adaptation
Which costs and capabilities belong to training before deployment versus changes during operation?
operating system or living substrate
Online adaptation
Valid claim: Changes state during operation under the declared feedback.
Comparable axes
- Information available
- Update budget
- Held-out future performance
Non-equivalences
- Pretraining cost cannot disappear from lifecycle accounting.
- State drift is not necessarily learning.
Comparison procedure
- 1.Separate phases.
- 2.Freeze feedback.
- 3.Test retention and transfer.
Prohibited inference
Do not call any online state change learning unless it improves a preregistered held-out outcome beyond drift, damage, repeated exposure, and controller-only controls.