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No way. The parameter count can't fit on consumer devices, and you're not getting orders of magnitude smarter behavior with smaller models.
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Do we actually know enough about neural networks to be able to say how many parameters you need for a given performance? I’m under the impression that we’re still in the phase of trying things out and we can’t rule out different architectures massively reducing computational needs.
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Parameter count is basically storage. Including persistent like flash memory. Which (still) is subject to Moore's law.

That's discounting architectural innovations & improvements which are bound to happen somehow.

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In 5 years phones can easily have 1 TB flash
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