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    AI-made annotations could offer a path to cheap, fast specialized AI, a user suggests

    One user argues that a capable general-purpose model could create annotations more accurately, faster and more cheaply than humans, making those annotations useful for training specialized AI.

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    TLDR

    A user suggests using annotations from a capable general-purpose model to develop narrow AI through distillation—using one model to train another. They see this as a route to cheap, fast specialized intelligence, arguing that the general model could produce annotations more accurately, faster and more cheaply than humans.

    Combined views

    107.5K

    3 Sources, first seen 23d ago

    Combined views

    107.5K

    3 Sources, first seen 23d ago

    999 likes
    23d ago
    first seen 23d ago
    999 likes
    51 comments
    416 saves
    74 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    51 comments
    416 saves
    74 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    3 Sources

    @SentdexLocal models can do ~ 3 Hz right now of tracking+intelligence (GLM 5.3 Flash, Qwen Next Flash, DSV4F-vision) We're probably 1 year or less away from Astra level intelligence running 10-30 Hz with <200ms latency. Plan accordingly.
    @BorisMPowerIt seems like an approach like this where the general very smart model creates annotations more accurately, faster and cheaply than humans solves for creating cheap and fast narrow intelligence through distillation!
    @yacineMTBRT @Sentdex: Local models can do ~ 3 Hz right now of tracking+intelligence (GLM 5.3 Flash, Qwen Next Flash, DSV4F-vision) We're probably 1…

    3 Sources

    @SentdexLocal models can do ~ 3 Hz right now of tracking+intelligence (GLM 5.3 Flash, Qwen Next Flash, DSV4F-vision) We're probably 1 year or less away from Astra level intelligence running 10-30 Hz with <200ms latency. Plan accordingly.
    @BorisMPowerIt seems like an approach like this where the general very smart model creates annotations more accurately, faster and cheaply than humans solves for creating cheap and fast narrow intelligence through distillation!
    @yacineMTBRT @Sentdex: Local models can do ~ 3 Hz right now of tracking+intelligence (GLM 5.3 Flash, Qwen Next Flash, DSV4F-vision) We're probably 1…