Rough thinking: neural nets are very tolerant of noise, so chopping off mantissa bits is akin to small amounts of noise. So I'd rather lose nearly all mantissa bits before losing exponent bits. So tried dropping 16 mantissa bits & model trained just fine w/ half the bandwidth.

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