3 ms·
that seems a bit harsh dont you think? besides youre the one making the assertion, you kinda need to do the proving ;)
by globalnode 2y ago
that seems a bit harsh dont you think? besides youre the one making the assertion, you kinda need to do the proving ;)
- jcgrillo 2y agoNo, I don't think it's overly harsh. This hype is out of control and it's important to push back on breathless "exponential" nonsense. That's a term with well defined easily demonstrated mathematical meaning. If you're going to claim growth in some quantity x is exponential, show me that measurements of that quantity fit an exponential function (as opposed to some other function) or provide me a falsifiable theory predicting said fit.
- kingkongjaffa 2y agoI believe they are using 'exponential' as a colloquialism rather than a strict mathematical definition. That aside, we would need to see some evidence of AI developments being bootstrapped by the previous SOTA model as key part of building the next model. For now, it's still human researchers pushing the SOTA models forwards. When people use the term exponential I feel that what they really mean is 'making something so _good_ that it can be used to make the N+1 iteration _more good_ than the last.
- cubefox 2y ago> It's a bit crazy to think AI capabilities will improve exponentially. I am a very reasonable person, so I just think they'll improve some amount proportional to their current level. https://www.lesswrong.com/posts/qLe4PPginLZxZg5dP/almost-all-growth-is-exponential-growth https://www.lesswrong.com/posts/qLe4PPginLZxZg5dP/almost-all...
- flux3125 2y ago>No, I don't think it's overly harsh. Where's the falsifiable framework that demonstrates your conclusion? Or are we just supposed to trust your intuition?
- brookst 2y agoWhy is it “important to push back”? XKCD 386?
- sandworm101 2y agoWell, any shift from "not able to do X" to "possibly able to do X sometimes" is at least exponential. 0.0001% is at least exponentially greater than 0%.
- jcgrillo 2y agoI believe we call that a "step change". It's only really two data points at most so you can't fit a continuous function to it with any confidence.