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    PROWL-2 introduced as a recursive-learning approach for agents and their world model

    Odyssey says agents expose errors in imagination, and repairing those errors enables further learning.

    OC
    OD
    3 Sources, ,

    TLDR

    Odyssey introduced PROWL-2 on October 1, describing a process in which agents and their world model improve through recursive learning. It says agents expose errors in imagination that can be repaired to enable further learning. Odyssey believes this open-ended learning is a critical step toward superintelligence.

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    3 Sources, first seen 4h ago

    Combined views

    16.9K

    3 Sources, first seen 4h ago

    215 likes
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    9 comments
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    3 Sources

    @odysseymlToday we’re introducing PROWL-2, where agents and their world model improve through recursive learning. Agents expose errors in imagination, and repairing those errors enables further learning. We believe this open-ended learning is a critical step towards superintelligence.
    @olivercameronRT @odysseyml: Today we’re introducing PROWL-2, where agents and their world model improve through recursive learning. Agents expose error…

    3 Sources

    @odysseymlToday we’re introducing PROWL-2, where agents and their world model improve through recursive learning. Agents expose errors in imagination, and repairing those errors enables further learning. We believe this open-ended learning is a critical step towards superintelligence.
    @olivercameronRT @odysseyml: Today we’re introducing PROWL-2, where agents and their world model improve through recursive learning. Agents expose error…