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    The potential scope of AI training with verifiable rewards beyond math and coding

    One post challenges the idea that AI’s uneven strengths depend on how verifiable a field is, pointing instead to “information asymmetry” as the more general ingredient.

    KA
    1 Source, 19d ago, first seen 19d ago

    TLDR

    A user questions whether reinforcement learning with verifiable rewards (RLVR) is limited to fields resembling math or software engineering. They propose “information asymmetry”—differences in who knows what—as the general ingredient, arguing that it can almost always be manufactured.

    Combined views

    14.3K

    1 Source, first seen 19d ago

    Combined views

    14.3K

    1 Source, first seen 19d ago

    333 likes
    333 likes
    16 comments
    108 saves
    13 reposts

    Sentiment

    Positive——Negative

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    No sentiment analysis available yet.

    16 comments
    108 saves
    13 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    1 Source

    @kalomazei'm becoming more opposed to the intuition people have wrt "spiky capabilities are a function of how verifiable a domain is",the idea that things not shaped like math/SWE won't fall to RLVR the general primitive is information asymmetry and you can almost anyways manufacture it

    1 Source

    @kalomazei'm becoming more opposed to the intuition people have wrt "spiky capabilities are a function of how verifiable a domain is",the idea that things not shaped like math/SWE won't fall to RLVR the general primitive is information asymmetry and you can almost anyways manufacture it