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    The training challenge for proactive AI agents outside coding

    A user argues that proactive agents need different reinforcement-learning rewards from agents trained to complete prompted tasks.

    MN
    2 Sources, 1h ago, first seen 1h ago

    TLDR

    A user says they have yet to see a non-coding agent product where most actions happen without a human prompt. They argue that proactive agents need reinforcement-learning environments and rewards suited to decisions such as when to follow up, whether to send a late-night message and how to communicate with different people. They say they know of no training pipeline for those social judgments.

    Combined views

    460

    2 Sources, first seen 1h ago

    Combined views

    460

    2 Sources, first seen 1h ago

    7 likes
    7 likes
    1 comments
    1 comments
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    2 Sources

    @menhguinjust realised the reason "proactive background agents" aren't very good: i've never seen a single RL environment for good proactive background agents. for the complexity involved, there's rly not much RL out there. and rewards are fundamentally different vs task completion.1h

    2 Sources

    @menhguinjust realised the reason "proactive background agents" aren't very good: i've never seen a single RL environment for good proactive background agents. for the complexity involved, there's rly not much RL out there. and rewards are fundamentally different vs task completion.1h
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