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The Sell ∀ ∃ as ∃ ∀ Scam

win-vector.com

51–60 of 148 posts

Re: The Sell ∀ ∃ as ∃ ∀ Scam

#51
post #9

I can walk and chew bubble gum at the same time: on one hand, yes, there's certainly a lot of Kool-Aid being drank by the AI folks. Even on HN, I constantly argue with people that genuinely think LLMs are some kind of magical black box that contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain. And on the other hand, I think that language interfaces are probably the n…

>it's just a very fancy Markov chain

Could you provide an argument for why an LLM is a fancy markov chain that does not apply equally well to a human?

Re: The Sell ∀ ∃ as ∃ ∀ Scam

#52

My biggest takeaway from the article is my new favorite word: cryptomorphic, meaning equivalent, but not obviously so.

I'm no linguist but it seems to me that that word doesn't really work for that definition. It sounds like it should pertain to hidden form, not hidden similar form, like say, cryptoisomorphic.

Re: The Sell ∀ ∃ as ∃ ∀ Scam

#53
post #29

Are compilers a scam as well? There exists a program every problem you have, you just have to find the code.

Crucially there is not a program for every problem. Many (presumably "Almost all" in a mathematical sense) problems are Undecidable and so a program can't do that.

Why are we not OK with the program producing the undecidability result?

Re: The Sell ∀ ∃ as ∃ ∀ Scam

#55

>To conclude: one must have different standards for developing systems than for testing, deploying, or using systems. Or: testing on your training data is a common way to cheat, but so is training on your test data. Isn't this already a solved problem? Every reasonable paper on ML separates their test data from their validation data already.

That in no way prevents overfitting though hyperparameter optimization / graduate student descent. All the common benchmarks, by definition of being a common benchmark, are susceptible to overfitting

The idea is that you do all your hyperparameter optimization with the test data and then only run through the validation data once before you submit your paper.

Re: The Sell ∀ ∃ as ∃ ∀ Scam

#59

If I understand correctly, the meat of the argument is "that is a system for every (∀) task, there exists (∃) a setting that gives the correct answer for that one task." My understanding of this (correct me if I'm wrong) is that the scam is convincing users that GPT-X can do anything with say, the correct prompts. This argument misses the mark for me. It's not that it solves all the problems, it's that the problems i…

Right #1 it’s not clear that this ∃ ∀ construction is a fair representation of what is being ‘sold’ by GPT-x #2 it’s also not clear what this proposed inverted formulation (∀ ∃) that describes what the author thinks GPT actually is even means. For every setting there exists a task that it answers? Does that even make sense?

Pretty sure you should read "for every task there exists a setting".
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