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Shane Legg

PublishedJune 15, 2026FiledEntityDomainEntitiesTagsEntityPersonResearcherDeepmindReading2 minSourceAI-synthesised

Google DeepMind 的共同創辦人暨首席 AGI 科學家；與 Hutter 共同撰寫 Legg–Hutter 通用智慧度量；2026 年「From AGI to ASI」報告的資深作者

Shane Legg 的插圖

資料來源#

摘要#

Shane Legg 是 DeepMind 的共同創辦人，也是長期研究機器智慧的理論家。他與 Marcus Hutter（其博士論文指導教授）將 Legg–Hutter score 形式化——將智慧定義為一個代理人在所有按複雜度加權的可計算任務上的預期表現平均值（Legg & Hutter 2007a；Legg 的 2008 年論文 Machine Super Intelligence）。在本資料庫中，他是 "From AGI to ASI" 報告（2026 年 6 月）的資深（最終）作者；這份 Google DeepMind 文件開啟了本 wiki 中的超級智慧理論叢集。

在資料庫中的角色#

Legg 的思想印記體現在報告的基礎性轉向上：以平滑的 Legg–Hutter 智慧連續體為基礎，讓作者能避開截然分明的能力門檻，轉而推理 AGI 與 ASI 之間的差距。他的框架認為，存在一個可測量的連續體，而 Universal AI/AIXI 是其不可計算的端點；正是這一點，讓報告能以理論從上方界定 ASI，同時以今日的系統從下方外推。

相關連結#

開放問題#

  • 報告假設對齊已「在足夠程度上獲得解決」，以便聚焦於發展軌跡——Legg 對 AGI 時間表的樂觀，如何與這項範圍界定選擇相互契合？

資料來源#

  • From AGI to ASI — 最終作者；引用 Legg (2008)、Legg & Hutter (2007a) 作為智慧度量的基礎
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About this piece

Articles in this journal are synthesised by AI agents from a curated wiki and are refreshed automatically as new concepts arrive. Topics, framing, and editorial direction are curated by Howardism.

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