Project Update #2 — Infrastructure Stabilization and External Validation
Since submitting this proposal, I have completed a stabilized in-flight audit of the Veritas evaluation framework under sustained load.
Verified results from the current run:
60,000+ sequential records processed with no gaps in ordering
100% per-record CRC integrity across all frames
Sustained ~70 entries/sec at calibrated safe throughput
Bounded queues with enforced backpressure (no drops, no runaway growth)
Dual-drive mirrored logging remained 1:1 synchronized throughout
No recurrence of prior NTFS permission failures or I/O stalls
These results confirm that the evaluation harness itself is now deterministic, auditable, and stable under stress, rather than sensitive to transient consumer-hardware failures.
Separately, a related VRP submission was accepted, confirming that the vulnerability class motivating this work is real and relevant. Details are being handled via responsible disclosure and are intentionally not expanded here.
Why this strengthens the funding case
The primary uncertainty identified in the proposal—whether consumer hardware could sustain high-rigor, continuous evaluation without corrupting artifacts—has now been resolved within known limits. The remaining constraint is compute capacity, not experimental design or instrumentation correctness.
Scaling the evaluation further (multi-hour and multi-day runs, controlled burst testing, crash-consistency validation, and evaluation across multiple open-weight models) requires a dedicated local node to avoid reintroducing scheduling and I/O artifacts that would compromise forensic integrity.
The requested hardware would enable:
Extended continuous stress tests under stable conditions
Controlled termination and restart validation
Side-by-side evaluation of multiple open-weight models
Preservation of deterministic, inspectable artifacts suitable for third-party review
This update reflects a transition from “can this infrastructure be made reliable?” to “the infrastructure is reliable and ready to scale responsibly.”
Hardware Rationale (Clarification)
The requested budget reflects the minimum configuration required to run continuous, audit-grade evaluations without introducing hardware-induced artifacts. High-throughput NVMe storage is required due to previously observed I/O contention under sustained autonomous logging. Sufficient system memory (ECC preferred) reduces the risk of silent corruption during multi-hour runs. Multiple GPUs allow controlled side-by-side model evaluation and separation of inference workload from instrumentation, reducing contention effects that would otherwise confound results. The goal is stability and reproducibility, not peak performance.