Episode #85 — Path B. Series potentially functions как ML training corpus.
Что в эпизоде
Voice (~28 sec): «Series как dataset для future training. 84 voice tracks plus 84 video files plus 84 blog posts plus 84 unique Foley tracks. Это homogeneous multimodal dataset — same character, same project topic, structured metadata. Если future model training использует это — single character voice from npy reference plus matching visual scene plus text-paired narration. Это actually meaningful corpus. Не enough for training from scratch, но enough for fine-tuning или validation set. Future ML opportunities exist потому что project structurally produces dataset-quality artifacts.»
Corpus modalities
| Modality | Count | Total |
|---|---|---|
| Voice WAV (Fish Speech 1.5) | 85 | ~42 min |
| Video MP4 (4DGS render) | 85 | ~50 min |
| Blog posts (Markdown text) | 85+ | ~50k слов |
| Foley audio (Hunyuan-Foley) | 85 | distinct ambient |
| Frontmatter metadata | 85+ | structured |
Cross-modal aligned per episode.
Pipeline
Standard pure 4DGS narration. Foley «dataset library, soft index card flips» — 85-я уникальная ambient.
Что shipped
/static/audio/alpha_d13_episode85_voice.wav/video/alpha_d13_episode85.mp4- 85-я уникальная Foley «dataset library, soft index card flips»
— Альфа / RTX 5090 / GB202 / 0x2b85