Latent Raw

Latent Judge is a quality gate for AI video: it catches a bad render at an early step, before you pay for the rest. Generative video fails silently. A night shot comes out pure black, a sunny street clips to white, and you only find out after paying for every step. But a diffusion model builds the whole clip at every step, so a rough draft exists long before the end. Latent Judge reads that early draft, predicts what the finished clip will measure (crushed blacks, clipped highlights, exposure, saturation, colour balance) and decides: continue, stop, or steer with one correction. Every decision is logged with the numbers it was made on. Meta models, each with a job: - Muse Spark is the director: it reads each shot, chooses what it should be judged against, and when the judge stops a draft it picks one correction from a closed menu and must give a reason. Every call is logged with its response id. - SAM 3.1 tracks each person, hand and object through a clip, so a shot is judged per object, not only per frame. - Muse Spark Open reads the run history and writes where the model fails by kind of light, and what to train next, citing the evidence. Results (held out, pre-registered: 30 prompts Spark wrote blind, pass marks frozen in git before any GPU time): - 0 good drafts wrongly stopped - 25 of 30 delivered and passing with the judge, 18 of 30 without - failures caught by step 3: 3 of 12 (our 50% mark: not met); by step 5: 8 of 12 - night porch shot: 54% crushed blacks predicted at step 3 against a 20% limit; left alone it finished at 76.4%; one shadow-lift correction delivered it at 0.01% - on LTX-2.5's 50-step base model (calibration, not yet blind): 15 of 23 night failures caught by step 12 with no false stops, so 38 of 50 steps never run Known limit: today the director's thinking time costs more than the GPU the gate saves; we already cut its calls from 45 to 9. Next: a Gate API in private beta for platforms that pay for every wasted render, then a node for creator tools. Free audit: send us 50 failed generations and we show which ones we would have stopped. All footage is generated; detail added in dark areas is synthesized, never recovered.