▲ | Jerrrry a day ago | |
I would use Floating Point arithmetic as the example/analogy: one trades off accuracy/precision for exactness/correct-ness when in the extremities. Answers near the more granular representations will be only be able to represented by their nearest value. If this is forsee-able, the floating point implementation can be adjusted to change where the floating point's "extremities'" are.I used the above analogy and the following when articulating the magnitude of near-lossless-ness that large LLM's have managed to attain, especially when all of the humanities corpus is compressed into a USB flash drive; the Kolmogorov complexity re-mitted/captured is similar to a master-piece like the Mona Lisa having to be described in X many brush-strokes to achieve Y amount of fidelity. |