jcp-efficiency: Seal a training run measured energy as training/1 #44
2026-07-22
jcp-efficiency: Seal a training run's measured energy as training/1
Every lab racing to ship models publishes efficiency in some unit that is not energy — parameters, throughput, tokens, or a flat "runs on your hardware" that quietly moves the electricity bill onto the buyer with no meter attached. The one number nobody publishes is joules per token trained. This receipt seals it. training/1 is the inference-side efficiency/1 turned to face the other direction: the same honest-provenance energy (measured/modeled/est., never overclaimed), the same JCR-1 sealing, the same hash-chaining, the same optional attestation binding. What it adds is the training-specific commitments — the base weights, the dataset, and the resulting weights are each a content id, so a set of trained weights carries verifiable evidence of what it cost to produce AND what data produced it. The dataset id is joule_core::training's corpus digest, so the chain runs from a verified run through the corpus to the weights it trained. Every commitment is load-bearing: a test flips one envelope byte and verification fails, so the receipt cannot be lifted onto different weights or a different dataset. The energy provenance is recomputed on read and a modeled (FLOP-estimated) run seals as modeled, never as measured — the honest-provenance rule the whole family turns on, applied to the number the industry most wants to fudge. Increment 2 of the training platform: the metered-training receipt. This is the training-side energy gap prior landscape scans repeatedly flagged as the single most strategically important and entirely uncontested. Co-Authored-By: Claude Opus 4.8 <[email protected]>