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Diffstat (limited to 'ROADMAP.md')
| -rw-r--r-- | ROADMAP.md | 10 |
1 files changed, 9 insertions, 1 deletions
@@ -341,12 +341,20 @@ claim is explicitly computational rather than a fit to cortical data. `ORAL_A.md` froze a validation-only ResNet-20 development funnel. A1 passed with `91.62%` BP validation accuracy. A2b selected channel-gated SDIL at `41.98%`, ahead of tuned DFA at `37.16%`, on the 10k/20-epoch screen. In full A3, DFA -ended finite at `33.06%`; SDIL became nonfinite at epoch 90 and ended at +ended finite at `33.06%`; SDIL became nonfinite at epoch 89 and ended at `10.00%`, failing alignment, accuracy, and finiteness gates. The MAC gate alone passed. Per the stop rule, the five-seed ResNet-20/32/56 test panel was never run. The exact BatchNorm/local-gradient mechanics remain verified, but the current training recipe does not establish standard-network scaling. +Post-failure diagnosis is recorded separately in +`results/oral_a_failure_diagnosis.json`: prediction--target cosine remains +below `8.51e-5` in magnitude, calibration MSE is indistinguishable from target +power, and target power grows `2.13e9x` before nonfiniteness. The next +development branch must therefore reduce causal-estimator variance in the +representable channel-gated subspace; changing only the v1 threshold is not an +allowed response. + Prepare convolutional local-update primitives and ResNet-20/32/56 protocols early. Queue frozen runs opportunistically on authorized idle GPUs. Because BurstCCN already reports CIFAR-10 and ImageNet scaling, dataset scale alone is not novel. The oral-level target is a memorable joint |