🧪 勝敗予測ラボ
試合を生成し、過去70%からプロフィールを作り、未来30%を予測するモデルを学習 — すべてブラウザ内で。
💡 なぜGPUが不要？
- Logistic regression has 15 parameters; even the deep MLP has ~2.2k — 100k matches of data is just a few MB.
- One epoch is millions of multiply-adds — milliseconds to seconds in a modern JS engine (see measured times above).
- At this scale WebGL/WebGPU kernel-dispatch overhead actually loses to plain CPU TypeScript.
- A real community produces hundreds to thousands of games — full retraining after every match stays under 100ms.