BluesF

Average is also a word used outside the context of mathematics. Would you make this argument if someone said "I'm average looking"? No, no, you can't be average looking, because there is no such thing as an average of appearances! Come on.

average as in typical or usual to what? what’s the data set?

The data set is the training set of the LLM. Look I get that you are obviously very against AI, and that's fine, I don't really care, but what they do is what I've described. It's not a literal average, no, but its comparable. That is all I have been trying to say.

Are you actually reading my comments? I am categorically NOT saying anything about mathematical averages, as I have said repeatedly. I am saying that what LLMs do is produce something that is akin to a mathematical average, when applied to text. It produces a "most likely" text output. That is all.

The word "average" does not always apply to numbers. You might, in some contexts, describe an "average" response to a survey - e.g. an opinion that would be considered the norm based on that survey. That is what I am describing. Average, as in "typical or usual."

I agree, which is why I find the results they got interesting, the fact that the initial study was able to, arguably quite correctly (well, debatable if it was correct, as I pointed out their results are not the easiest to evaluate), predict real results is pretty impressive.

Yes, I understand that, you are not understanding what I'm describing. I am not talking about taking an average of numerical data. LLMs take something that can be thought of as an "average" of text. It says "given all the text I have seen, and this new text input, what's the most likely output?" In some numerical contexts the expected value is also an average, LLMs find a similar result, and that is what I am drawing a parallel between here.

Yes, it can obviously never entirely replace real surveys. I would assume that survey results forming a part of the training set is a big part of why they're able to get good results in the first place, and as I said I think its a significant risk that the evaluation is done it performs well because the data being evaluated against are (unbeknownst to the researcher) present in the training set.

I think I was overall pretty critical of the idea? I just find it interesting.

That's a good point, although I imagine a dedicated company could refine a model using more recently sampled general data to improve the recency.

I'm not talking about numerical data, the way LLMs work is to find a "most likely response" based on the input text. There is absolutely maths happening inside the model, how else do you think they work? I'm not saying they take numbers and find an average.

I think what makes time really fly is boredom. Not necessarily like, waiting for a train or whatever, but more like "I do the same thing every day" exhaustion with life. The past couple of years have flown by for me but it's 100% because I don't like my current job and I don't do a lot else recently. The more I like my 9-5, and the more the rest of my life excites me, the more memories I get and the longer time seems to take to pass.

It's no surprise that for most people this happens in your late teens/early 20s, you're meeting new people all the time, you maybe go to university, you go to parties, and so on. If you stop doing that as you get older and don't start anything else its inevitable that time will just start to get away from you.

I propose the slaves eat their masters

I would argue it is either 1) neither necessary nor sufficient, or 2) that it is sufficient but not necessary. Which line depends on whether we are talking about something literally BEING a meme, or something merely having the potential to be a meme.

In the former case - whether something is a meme or not - having text is neither necessary nor sufficient. Adding text to an image does not a meme make, and equally some memes do not have text (or aren't images at all).

In the latter - whether something could be a meme - adding text is sufficient to provide that potential. It may not be necessary (6-7 for example) but it could be enough.