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    Two readings of AI models getting 'predictably better with scale'

    A commenter contrasts bigger models almost always outperforming smaller ones with drawing meaningful conclusions about big models from small ones.

    Diyi YangDY
    Will Held @ COLM 6-8WH
    2 Sources, 3h ago, first seen 3h ago

    TLDR

    In a reply, a commenter distinguishes two readings of “predictably better with scale”: bigger models almost always outperform smaller ones, or improvements are predictable enough to say meaningful things about big models from small ones.

    Combined views

    460

    2 Sources, first seen 3h ago

    Combined views

    460

    2 Sources, first seen 3h ago

    11 likes
    11 likes
    1 comments
    3 reposts
    1 comments
    3 reposts

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    2 Sources

    Will Held @ COLM 6-8@WilliamBarrHeld@giffmana @dlwh @percyliang @Diyi_Yang Part of the issue is how people interpreted the core idea: Models get predictably *better with scale* (a big model will ~always be better than a small one) vs. Models get *predictably* better with scale (you can say meaningful things about big models from small ones)3h
    Diyi Yang@Diyi_YangRT @WilliamBarrHeld: @giffmana @dlwh @percyliang @Diyi_Yang Part of the issue is how people interpreted the core idea: Models get predicta…2h

    2 Sources

    Will Held @ COLM 6-8@WilliamBarrHeld@giffmana @dlwh @percyliang @Diyi_Yang Part of the issue is how people interpreted the core idea: Models get predictably *better with scale* (a big model will ~always be better than a small one) vs. Models get *predictably* better with scale (you can say meaningful things about big models from small ones)3h
    Diyi Yang@Diyi_YangRT @WilliamBarrHeld: @giffmana @dlwh @percyliang @Diyi_Yang Part of the issue is how people interpreted the core idea: Models get predicta…2h