both those are related to information theory, but there are other things I legally can’t mention. shrug.
hahahaha fuck off with this. no, the horseshit you’re fetishizing doesn’t fix LLMs. here’s what quantization gets you:
- the LLM runs on shittier hardware
- the LLM works worse too
- that last one’s kinda bad when the technology already works like shit
anyway speaking of basic information theory:
but the research showing that 3 bits is as good as 64 is intuitive once you tie the original inspiration for some of the AI designs.
lol
It’s actually super easy to increase the accuracy of LLMs.
import pytorch # or ollama or however you fucking dorks use this nonsense
from decimal import Decimal
I left out all the other details because it’s pretty intuitive why it works if you understand why floats have precision issues.
I have seen these 3 bit ai papers on hacker news a few times. And the takeaway apparently is: the current models are being pretty shitty at what we want them to do, and we can reach a similar (but slightly worse) level of shittyness with 3 bits.
But that doesn’t say anything about how both technologies could progress in the future. I guess you can compensate for having only three bits to pass between nodes by just having more nodes. But that doesn’t really seem helpful, neither for storage nor compute.
Anyways yeah it always strikes me as a kind of trend that maybe has an application in a very specific niche but is likely bullshit if applied to the general case
If anything that sounds like an indictment? Like, the current models are so incredibly fucking bad that we could achieve the same with three bits and a ham sandwich
