Live data from Hacker News

ChatGPT Explained: A normie's guide to how it works

jonstokes.com

1–10 of 144 posts

Re: ChatGPT Explained: A normie's guide to how it works

#3
I posted some comments about ChatGTP in a local FB group and there was a pretty large percent of folks who responded here that think it's just an awful thing that's going to lead to the downfall of civilization.

I tried to offer that it is pretty cool, but it's just software that basically presents search engine results in a different manner along with a few other tricks, but it's not "HAL".

I live in a very red and rural area so that probably has something to do with it. They love to have new things to complain about that have no effect on any of us at all.

Re: ChatGPT Explained: A normie's guide to how it works

#4
I feel like as an intro aimed at "normies" it still manages to communicate in a more abstract and overthinky way than necessary.

People often find it difficult to intuit examples from abstract descriptions. BUT, people are great at intuiting abstractions from concrete examples.

You rarely need to explicitly mention abstractions, in informal talk. People's minds are always abstracting.

> If I’m relating the collections {cat} and {at-cay}, that’s a standard “Pig Latin” transformation I can manage with a simple, handwritten rule set.

Or...

"Translating {cat} to {at-cay}, can be managed with one “Pig Latin” rule:

  If input is {cat} then output is {at-cay}."
"Translate" is normie and more context specific to the example than "transformation". "Set" is not "normie" (normies say "collection"), and its superfluous for one rule.

Concrete, specific, colloquial, shorter, even when less formally correct, all reduce mental friction.

Re: ChatGPT Explained: A normie's guide to how it works

#5
I like the token window bit. I don't really like the probability bit, because it kinda alludes that OpenAI just built a huge probability map of all N-grams (N=8000) and called it a day.

Which incidentally would also imply that a lot of N-grams just don't exist in the training data, causing the model to completely halt when someone says something unexpected.

But that's not the case - instead we convert words into a lot fuzzier float vector space - and then we train the network to predict the next fuzzy float vector. Since the space is so vast, to do this it must learn the ability to generalize, that is, to extrapolate or interpolate predictions even in situations where no examples exists. For this purpose, it has quite a few layers of interconnects with billions of weights where it sums and multiplies numbers from the initial vectors, and during training it tries to tweak those numbers in the general direction of making the error of its last predicted word vector smaller.

And since the N-gram length is so long, the data so large, and the number of internal weights is so big, it has the ability to generalize (extrapolate) very complex things.

So this "probability of next word" thing has some misleading implications WRT what the limits of these models are.

Re: ChatGPT Explained: A normie's guide to how it works

#6
The biggest drawback of LLM is that it never answers with "I don't know" (unless it is some quote) and it just brings bullshit hallucinations which human has to reject as wrong. Thus it is mostly useless for anything serious. Personally I use it to beautify some text, but still have to do a bit of correction to fix b/s or missed context.

Re: ChatGPT Explained: A normie's guide to how it works

#7
post #3

I posted some comments about ChatGTP in a local FB group and there was a pretty large percent of folks who responded here that think it's just an awful thing that's going to lead to the downfall of civilization. I tried to offer that it is pretty cool, but it's just software that basically presents search engine results in a different manner along with a few other tricks, but it's not "HAL". I live in a very red and…

> I live in a very red and rural area so that probably has something to do with it. They love to have new things to complain about that have no effect on any of us at all.

That seems an ungenerous interpretation. I don't doubt that their understanding is full of science-fiction inspired fear, but the implications and dangers of this tech is a hotly debated topic among informed experts. So, even if their specific fears are ungrounded, their fear may not be (ie, effects on the economy, culture, education, especially as the tech advances, which it will).

Re: ChatGPT Explained: A normie's guide to how it works

#8
post #2

I recommend: ChatGPT Is a Blurry JPEG of the Web by Ted Chiang https://www.newyorker.com/tech/annals-of-technology/chatgpt-...

Your recommended article is more of a critique than OPs "GPT for dummies", and very unsuccessful at explaining what's going on in that chatbox.

Re: ChatGPT Explained: A normie's guide to how it works

#10
post #2

I recommend: ChatGPT Is a Blurry JPEG of the Web by Ted Chiang https://www.newyorker.com/tech/annals-of-technology/chatgpt-...

Disagree.

As far as I understand, in this article he argues that in the, say, ChatGPT output, compression happens.

But does it really?

To make a similarly low resolution metaphor, a “bayesian kaleidoscope” of a language model doesn’t necessarily mean it blurs the “word pixels” it is moving around. Because moving them around, rearranging them is what it essentially does, even if in opaque ways; but not degrading them, not changing letters in words or deliberately algorithmically messing up the word order in a sentence.

To make sense of the “image” an LLM produces is left up to us, and therefore, it is also up to us to decide whether any compression of anything has happened. And then, how do you measure it?

If you cut a painting into pieces, then glue them back together at random, thus making a new painting, would that constitute a “compression” or just a new painting, which could be worse or better than the original?

I quite like Chiang’s writing, but not this time. If anything, his take on this undermines what he previously wrote a little bit, painting him more of an LLM that he probably would like to admit :)

Post reply on HN