I would like to hear in what sense you love your kids, given that "he first six years have so far been very much a drag on my life and productivity, and not much else. They haven’t provided fulfilment, and they haven’t provided satisfaction. (...) Happiness for me typically starts after my kids are in bed or when I can escape them during work hours."
Do you say "I love my kids" because that's what everybody says, or is there any truth in it?
EDIT: Just to be 100% clear: I mean absolutely no judgement. I'm not going to tell you off or try to change your mind. I ask out of pure curiosity.
Could someone clarify for a linux newbie like me... In practical terms, what does this mean? I'm on Debian so presumably Debian will eventually pick this update, and then what? When I upgrade my system I'll get a prompt asking for my date of birth?
There is no burden of proof on me, because I'm not asserting that AI has invented something on its own. I haven't told you what my view is or whether I ever have a view.
The problem with the reasoning of the person I was responding to is that it's assuming "if X is in the training set and LLM outputs X, then it did so because X is in the training set". That does not follow. Conceivably it's possible that X is in the training set and LLM outputs X, but if X hadn't been in the training set the LLM also would've output X.
Lets look at that phrase again:
> Why do we think this emerged “on its own”? Surely this technique has been discussed in research papers that are in the training set.
This phrase implies "if X was in the training set, then LLM couldn't have come up with X on its own". This is false. In fact, my claim that the implication is false is testable, in the following manner: Have two training sets, T and T'. In T, X is present. In T' you've removed X but left X-adjacent things. Train LLM A on T and A' on T'. Find a prompt that requires that A outputs X. If on the same prompt A' also outputs X, that's an example of my claim. To repeat, my claim is "it's possible that X is in the training set and LLM outputs X, but if X hadn't been in the training set the LLM also would've output X."
In fact, I've just realized I even have a method for constructing (T, T') that guarantees what I've described. Not sure if it's worth a paper on its own though.
Reminder that when you use terminology like "sideloading" you're accepting the premise that there's something inherently dodgy about installing your software onto your operating system.
But before LLMs, computers couldn't understand that phrase. Now they can.