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Understanding ChatGPT

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Re: Understanding ChatGPT

#211

Post by teolandon »

notahacker wrote: post #117
teolandon wrote: post #109

Earlier quoted context omitted.

I've interacted with many people online, only through text, and my life has significantly changed because of many of those interactions. The effect on my life would have been the same whether the entities typing were made out of silicon or carbon.

Sure, and I've been deeply affected by books, but I'm not going to start using that as a basis for an argument a book and a human think in exactly the same way

This was in response to your comment about how you can tell that a water simulation is fake by trying to dip a water bottle in there. The distinction between chemical and silicon doesn't matter when the output is text. There's no physical test you can perform in the text, like dipping a water bottle in water, to see if it's chemical or silicon.

Re: Understanding ChatGPT

#212

Post by scotty79 »

stevenhuang wrote: post #205
scotty79 wrote: post #144

Earlier quoted context omitted.

It definitely means that it was thinking wrongly if at all. Just talk to GPT about math. You'll quickly change your mind about the possibility of it thinking.

LLMs are bad at arithmetic due to tokenization limitations but they're actually pretty decent at mathematical reasoning. You don't know what you're talking about I'm afraid. https://www.lesswrong.com/posts/qy5dF7bQcFjSKaW58/bad-at-ari...

Please just try. It's horrible at mathematical reasoning. Use just words to avoid problems with tokenization. Alternatively just read through the link you provided. It has many examples of failures of GPT and gabage it produces when talked to about math.

Re: Understanding ChatGPT

#213

Post by Blikkentrekker »

colonCapitalDee wrote: post #203
Blikkentrekker wrote: post #185

Earlier quoted context omitted.

> In this (and other comments by you I think?) you've implied the onus is on the AGI sceptics to prove to you that the LLM is not sentient (or whatever word you want to describe motive force, intent, consciousness, etc that we associate with human intelligence). This is an unreasonable request - it is on you to show that it is so. And yet, humans are assumed so without having to show it. Suppose a computer programmed…

So you're saying that LLMs are sentient because we can't prove that anything or anyone is sentient?

No, not at all. I'm purely saying that the argument that they are different from humans is not necessarily substantiated.

Re: Understanding ChatGPT

#214

Post by Blikkentrekker »

ak_111 wrote: post #190
Blikkentrekker wrote: post #177

Earlier quoted context omitted.

Universal grammar only speaks to the ability to parse and form sentences, not to internal logic. That ChatGPT is capable of producing human-like sentences from pattern recognition without any universal grammar baked in, even if the underlying reasoning might be flawed, goes against the argument of something such as universal grammar existing. At the very least, it shows that a neural net is capable of parsing and pro…

That ChatGPT is capable of producing human-like sentences from pattern recognition without any universal grammar baked in You didn't address or missed the main point: chatgpt requires something in the order of a trillion tokens to be capable of producing what you mentioned in one language. There are 40 months old babies that are fairly conversant in both Chinese and English, and are able to detect sarcasm with someth…

It requires so much to be able to generate answers tot hings asked about a wide variety of subjects, not to be able to generate grammatically valid sentences and parse them, which other a.i.'s also did before with far fewer tokens.

Re: Understanding ChatGPT

#215

Post by stevenhuang »

scotty79 wrote: post #212
stevenhuang wrote: post #205

Earlier quoted context omitted.

LLMs are bad at arithmetic due to tokenization limitations but they're actually pretty decent at mathematical reasoning. You don't know what you're talking about I'm afraid. https://www.lesswrong.com/posts/qy5dF7bQcFjSKaW58/bad-at-ari...

Please just try. It's horrible at mathematical reasoning. Use just words to avoid problems with tokenization. Alternatively just read through the link you provided. It has many examples of failures of GPT and gabage it produces when talked to about math.

Clearly you haven't read it then.

The provided example directly shows ability in mathematical reasoning by coming up with a novel concept and example case, it is just poor in arithmetic.

Math is not simply arithmetic abilities, you seem unable to comprehend this.

Re: Understanding ChatGPT

#216

Post by maxdoop »

mellosouls wrote: post #122
maxdoop wrote: post #28

“It’s a glorified word predictor” is becoming increasingly maddening to read. Do tell— how can you prove humans are any different? The most common “proofs” I’ve seen: “Humans are more complex”. Ok, so you’re implying we add more complexity (maybe more modalities?); if more complexity is added, will you continue to say “LLMs are just word predictors”? “Humans are actually reasoning. LLMs are not.” Again, how would you…

Do tell— how can you prove humans are any different? In this (and other comments by you I think?) you've implied the onus is on the AGI sceptics to prove to you that the LLM is not sentient (or whatever word you want to describe motive force, intent, consciousness, etc that we associate with human intelligence). This is an unreasonable request - it is on you to show that it is so. I’m forever amazed how a seemingly f…

There’s a misunderstanding here—

I’m not claiming LLMs are sentient. I’m not claiming they are even similar.

What I am pushing back against is the confidence with which people so blatantly claim we are dissimilar.

It’s an important distinction, and I’ve yet to see solid evidence to suggest it’s a point we shouldn’t even explore.

What I see so often is comments stating things like, “an LLM is just pattern matching” or “it’s a prediction machine”.

And I’m not arguing that’s not true; what I’m arguing is how can anyone say a human is inherently different ?

I admit that I’m taken with these latest advancements. It’s why yes, you see my tech-bro crazy-person comments in these threads a lot! But I’m genuinely fascinated by this stuff.

I have had a huge interest in the human mind for a decade. I’ve read the works of folks like Anil Seth and others who work in cognitive and computational science, and I’m increasingly intrigued by the things we might learn about our own selves via these technological advancements.

Again, I’m not claiming sentience for an LLM, or anything that says “we are the same as an LLM.” I’m simply trying to argue that our own minds are a black box, as are how an LLM arrives at an output; it’s the confidence of folks to claim they know what’s inside either that I’m pushing back against.

Re: Understanding ChatGPT

#217

Post by scotty79 »

stevenhuang wrote: post #215
scotty79 wrote: post #212

Earlier quoted context omitted.

Please just try. It's horrible at mathematical reasoning. Use just words to avoid problems with tokenization. Alternatively just read through the link you provided. It has many examples of failures of GPT and gabage it produces when talked to about math.

Clearly you haven't read it then. The provided example directly shows ability in mathematical reasoning by coming up with a novel concept and example case, it is just poor in arithmetic. Math is not simply arithmetic abilities, you seem unable to comprehend this.

Sure, sure.

"I want it to come up with a new idea. Its first attempt was to just regurgitate the definition of the set of zero-divisors (a very basic concept), and (falsely) asserted that they formed an ideal (among other false claims about endomorphism rings)."

"I tried a few more times, and it gave a few more examples of ideas that are well-known in ring theory (with a few less-than-true modifications sometimes), insisting that they are new and original."

"This in particular is quite an interesting failure. "

"So there we have it. A new definition. One example (of a 4-cohesive ring) extracted with only mild handholding, and another example (of a 2-cohesive ideal) extracted by cherry-picking, error-forgiveness, and some more serious handholding."

"Some errors (being bad at arithmetic) will almost certainly be fixed in the fairly near future." - and this opinion is based on absolutely nothing.

Re: Understanding ChatGPT

#218

Post by maxdoop »

jppittma wrote: post #154
maxdoop wrote: post #28

“It’s a glorified word predictor” is becoming increasingly maddening to read. Do tell— how can you prove humans are any different? The most common “proofs” I’ve seen: “Humans are more complex”. Ok, so you’re implying we add more complexity (maybe more modalities?); if more complexity is added, will you continue to say “LLMs are just word predictors”? “Humans are actually reasoning. LLMs are not.” Again, how would you…

No matter how much you explain to somebody what an apple tastes like, they'll never be able to truly know without having experienced it. Language is reductive on experience. Likewise, we have models like gravity that describe planetary motion. It is useful, but by nature of being a model, it's incomplete. Models are also reductive on experience. Can you see then how a large language model, something that describes an…

This is true, but I fail to see how something like qualia ( the subjective experience ) necessarily matters.

The thing I find interesting in the current LLM conversation is how much it’s opened up conversations around “what is knowing? What is consciousness?”

Does it matter, not philosophically but utility-wise, if something can give the illusion of intelligence or “knowing”?

And to go on something you said about taste— this is the age-old conundrum that still applies to humans, not just LLMs. I will never know if the color green to me is the same color as it is to you; our subjective experience may be entirely different, yet we both use the same language to describe what we experience.

And that language does the job just fine, even without the experience itself factored in.

Re: Understanding ChatGPT

#219

Post by maxdoop »

barrysteve wrote: post #126
maxdoop wrote: post #28

“It’s a glorified word predictor” is becoming increasingly maddening to read. Do tell— how can you prove humans are any different? The most common “proofs” I’ve seen: “Humans are more complex”. Ok, so you’re implying we add more complexity (maybe more modalities?); if more complexity is added, will you continue to say “LLMs are just word predictors”? “Humans are actually reasoning. LLMs are not.” Again, how would you…

I don't see why'd you have to prove humans are anything at all, to validate the claim that GPT is a word predictor. ChatGPT doesn't really need defending, the proof is in it's massive success.. right? It seems the news cycle has settled into two possible options for future code releases. It's either the second coming of Christ (hyperbolically speaking) or it's an overly reductive definition of GPT's core functionalit…

My point isn’t that LLMs are anything more than pattern predictors; it’s that calling them such as some sort of dismissal doesn’t really strike me as the “gotcha” it initially seems.

We don’t know that humans themselves aren’t just prediction machines. Yet , humans are insanely capable! And thus the same might apply to an LLM.

It’s hard to strike a balance between having excited, rational, discussion and not coming across like a religious AI nut.

Re: Understanding ChatGPT

#220

Post by barrysteve »

maxdoop wrote: post #219
barrysteve wrote: post #126

Earlier quoted context omitted.

I don't see why'd you have to prove humans are anything at all, to validate the claim that GPT is a word predictor. ChatGPT doesn't really need defending, the proof is in it's massive success.. right? It seems the news cycle has settled into two possible options for future code releases. It's either the second coming of Christ (hyperbolically speaking) or it's an overly reductive definition of GPT's core functionalit…

My point isn’t that LLMs are anything more than pattern predictors; it’s that calling them such as some sort of dismissal doesn’t really strike me as the “gotcha” it initially seems. We don’t know that humans themselves aren’t just prediction machines. Yet , humans are insanely capable! And thus the same might apply to an LLM. It’s hard to strike a balance between having excited, rational, discussion and not coming a…

Oohh it always struck me as the comparison to humans was to marginalize humans.

I'm often on the reductive "gotcha" side and it is always a rummaging around to find and understand the essence of the thing in front of me causing all this news and hype. Peel open the black box and see it's basic shape, as much as one can from the outside..

Thank you for the insight, I genuinely have been annoyed at people who are "dragging down The Human Consciousness to the level of basic boolean logic", when they compare computing to humans and I never got the other side of it.

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