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  • What would a Provably Safe AGI Framework look like?

    What would a Provably Safe AGI Framework look like?

    Xiaohu Zhu

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    Apr 8, 2024

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    AGI, AI Safety, Beneficial, CSAGI
  • AN #71 通过当下-RF优化避免奖励篡改

    Xiaohu Zhu

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    Nov 1, 2019

    ×

    AI Safety, Alignment
  • AN #68 影响的可获得效用理论

    Xiaohu Zhu

    —

    Oct 30, 2019

    ×

    AI Safety, Alignment
  • AN #67 创建在其中研究内部对齐故障的环境

    Xiaohu Zhu

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    Oct 30, 2019

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    AI Safety, Alignment
  • AN #66 将健壮性分解为能力健壮性和对齐健壮性

    Xiaohu Zhu

    —

    Oct 30, 2019

    ×

    AI Safety, Alignment
  • AN #65 通过观看人类‘玩游戏’学习有用的技能

    Xiaohu Zhu

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    Oct 30, 2019

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    AI Safety, Alignment
  • AN #64 使用深度强化学习和奖励的不确定性来激发偏好学习

    Xiaohu Zhu

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    Oct 30, 2019

    ×

    AI Safety, Alignment
  • AN #69 Stuart Russell 新书-为何我们需要替换人工智能标准模型?

    Xiaohu Zhu

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    Oct 30, 2019

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    AI Safety, Alignment
  • AN #70 帮助仍在学习自己的偏好的人类的智能体

    Xiaohu Zhu

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    Oct 30, 2019

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    AI Safety, Alignment
  • AN #63 架构搜索,元学习和环境设计可以怎样去产生通用人工智能?

    Xiaohu Zhu

    —

    Sep 12, 2019

    ×

    未分类
  • AN #62 对抗性样本是由真实但难以察觉的特征引起的吗?

    Xiaohu Zhu

    —

    Aug 23, 2019

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    AGI, AI Safety, Alignment
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