Episode Details

The experiment series reached a turning point: Joey watched the G-Stod 2020 volleyball finals live in Switzerland, then went home and fed that same match footage to the machine learning pipeline. This episode documents the technical breakthrough when AI analysis caught up to real-time—and what the cleanest scoreboard reads yet revealed about the project's trajectory. 00:00 - Correction: Attribution for AI contributions 01:15 - The bottleneck that just broke: from 50-minute manual capture to same-day pipeline 03:45 - Joey's Swiss Alps moment: watching volleyball live 05:30 - Pipeline staging chain: marking, scoreboard detection, whistle recognition 07:00 - The results: only 8 misreads across the entire match 09:20 - Evaluation: 10/10 accuracy on random spot-check clips 12:45 - What this win means for the next phase --- Sources & further reading: • game-senser-fable repo — docs/podcast/LEARNING-CONTEXT.md §7 ADDENDUM • (2026-07-27 evening: the dress-rehearsal split, the bar-presence discovery, the • reclassification) • game-senser-fable repo — JOURNAL.md 2026-07-27 entries + data/gstaad2026/STAGING.md • (staging chain, OCR quality, v2 windows) • game-senser-fable repo — data/gstaad2026/barpresence532121.json + • src/out/gstaadsample10v2verdicts.json + HUMANINPUT_LOG.md (the two 10-clip verdict • passes) • guist-bot repo — data/series/ml-volleyball/ERRATA.md (the ep-2 attribution correction • Joey's series directive on clip cutting) This podcast episode was fully generated by AI — research, script, voices, and production. Built with Claude, Piper TTS, and automated pipeline tooling.