Show HN：PSSU – AI 為何無法形成持久性身份（互動式演示）
Hacker News·
這篇 Hacker News 的「Show HN」文章介紹了 PSSU，一個探討 AI 為何難以形成持久性身份的互動式演示。文章對比了不同代理在身份保留與學習能力資源分配下的行為。
PSSU: Active Learning Window with LocalStorage Persistence
Performance Metrics Comparison (Real-time)
🔒 Frozen Agent (C=0.95, G=0.05)
Identity preservation consumes 95% of resources.
Only 5% available for learning. Result: Cannot adapt to changing environment.
Behavior: Repeats mistakes, rejects feedback, appears "certain" but wrong.
🌊 Dissolved Agent (C=0.20, G=0.80)
Identity too fluid, no stable foundation.
Forgets previous learning. Result: Chaotic, cannot maintain skills.
Behavior: Overwrites beliefs, performance oscillates, can't retain constraints.
⚖️ Bounded Agent (C=0.70, G=0.30)
70% identity preservation, 30% learning capacity.
Maintains core constraints while adapting. Result: Stable improvement with identity continuity.
Behavior: Learns while preserving constraints, improves monotonically.
相關文章