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Understanding ChatGPT

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Re: Understanding ChatGPT

#141

Post by procgen »

ak_111 wrote: post #138
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…

The strongest answer to almost all of your questions is "Poverty of the stimulus" (wikipedia). 4 year olds are exposed to an almost microscopically tiny amount of words relative to chatgpt (you can probably contain it in a csv file that you can open in excel), and yet can reason, even develop multilingual skills and a huge amount of emotional intelligence from the very little word tokens they are exposed to. So whate…

There's billions of years of compressed knowledge in those 4 year olds. Lots of useful priors.

Re: Understanding ChatGPT

#142

Post by ak_111 »

procgen wrote: post #141
ak_111 wrote: post #138

Earlier quoted context omitted.

The strongest answer to almost all of your questions is "Poverty of the stimulus" (wikipedia). 4 year olds are exposed to an almost microscopically tiny amount of words relative to chatgpt (you can probably contain it in a csv file that you can open in excel), and yet can reason, even develop multilingual skills and a huge amount of emotional intelligence from the very little word tokens they are exposed to. So whate…

There's billions of years of compressed knowledge in those 4 year olds. Lots of useful priors.

You basically landed on Chomsky's universal grammar. And this only proves the chatgpt critics: we have no idea what those priors are, how they evolved, why they are so effective and thus we are not even sure they exist. Until this is demonstrated I think it is very fair to say chatgpt is applying very different reasoning to what humans are applying.

Also language is a fairly recent development in human evolution (only 60-70 generations ago) which makes it much more puzzling how a mechanism that is so efficient and effective could evolve so quickly, let alone pondering how actual languages evolved (almost instantly all over the world) given how hard it is to construct an artificial one.

Re: Understanding ChatGPT

#143

Post by indymike »

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?

There likely is not a way to prove to you that human intelligence and LLMs are different. That is precisely because of the uniquely human ability to maintain strong belief in something despite overwhelming evidence to the contrary. It underpins our trust in leaders and institutions.

> ’m forever amazed how a seemingly forward-looking group of people is continually dismissive of a tool that came out LITERALLY 4 MONTHS AGO

I don't see people being dismissive. I see people struggling to understand, struggling to process, and most importantly, struggling to come to grips with the a new reality.

Re: Understanding ChatGPT

#144

Post by scotty79 »

aqme28 wrote: post #81
scotty79 wrote: post #76

Earlier quoted context omitted.

It's just wrong. That's how you can tell. Actual reasoning leads to sensible conclusions.

Coming to the wrong conclusion doesn’t mean I wasn’t thinking through the problem.

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.

Re: Understanding ChatGPT

#145

Post by tarsinge »

calf wrote: post #13

ChatGPT is a glorified word predictor. It isn’t sentient. It doesn’t know what it’s saying, and yes, you can coax it into admitting that it wants to take over the world or saying hurtful things (although it was specially conditioned during training to try to suppress such output). It’s simply stringing words together using an expansive statistical model built from billions of sentences. Is this true though? The publi…

I don’t see the problem with LLM having a world model and superhuman intelligence without sentience. It seems very unlikely sentience comes from computation and that it’s not a physical property: why would only certain Boolean or mathematical operations in a certain order make your pen, piece of paper or CPU see colors or hear sounds? That the operations you do follow a complex plan is irrelevant. Conversely if you do enough mindfulness you can attain a state of complete empty mind / "no computation" while still being physically there, and it would not be surprising some animals with a very limited intelligence and world model have sentience. The burden of proof is on sentience not being some kind of fundamental property of matter or EM fields for me.

Re: Understanding ChatGPT

#146

Post by sebzim4500 »

usaar333 wrote: post #137
sebzim4500 wrote: post #38

Earlier quoted context omitted.

I'm not surprised to see your comment be downvoted, but I have yet to see a single coherent answer to this. I wish people would be more clear on what exactly they believe the difference is between LLMs are actual intelligence. Substrate? Number of neurons? Number of connections? Spiking neurons vs. simpler artifial neurons? Constant amount of computation per token vs variable? Or is it "I know it when I see it"? In w…

Meta-awareness and meta-reasoning are big ones. Such inabilities to self-validate its own answers largely preclude human level "reasoning". It ends up being one of the best pattern matchers and translators ever created, but solves truly novel problems worse than a child. As far as architectural details, it's a purely feed forward network where the only input is previous tokens generated. Brains have a lot more going…

>Meta-awareness and meta-reasoning are big ones

Can you give an example a prompt that shows it does not have meta-awareness and meta-reasoning

>Such inabilities to self-validate its own answers largely preclude human level "reasoning".

I don't think it's true that it can't self-validate you just have to prompt it correctly. Sometimes if you copy-paste an earlier incorrect response it can find the error.

> but solves truly novel problems worse than a child.

Can you give an example of a truly novel problem that it solves worse than a child? How old is the child?

>As far as architectural details, it's a purely feed forward network where the only input is previous tokens generated.

True, but you can let it use output tokens as scratch space and then only look at the final result. That lets it behave as if it has memory.

> Brains have a lot more going on.

Certainly true, but how much of this is necessary for intelligence and how much just happens to be the most efficient way to make a biological intelligent system? Biological neural networks operate under constraints that artifial ones don't, for example they can't quickly send signals from one side of the brain to the other.

The idea that the more sophisticated structure of the brain is necessary for intelligence is a very plausible conjecture, but I have not seen any evidence for it. To the contrary, the trend of increasingly large transformers seemingly getting qualitatively smarter indicates that maybe the architecture matters less than the scale/training data/cost function.

Re: Understanding ChatGPT

#147

Post by belter »

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 would humbly submit these two examples, to claim at least for the moment, they are a kind of word predictor...

- https://news.ycombinator.com/item?id=35314634

- https://news.ycombinator.com/item?id=35315001

Re: Understanding ChatGPT

#148

Post by alcover »

ak_111 wrote: post #142
procgen wrote: post #141

Earlier quoted context omitted.

There's billions of years of compressed knowledge in those 4 year olds. Lots of useful priors.

You basically landed on Chomsky's universal grammar. And this only proves the chatgpt critics: we have no idea what those priors are, how they evolved, why they are so effective and thus we are not even sure they exist. Until this is demonstrated I think it is very fair to say chatgpt is applying very different reasoning to what humans are applying. Also language is a fairly recent development in human evolution (onl…

60-70 generations ago

More like 1000+ considering the Chauvet painters certainly had speech.

Re: Understanding ChatGPT

#149

Post by detrites »

dsiegel2275 wrote: post #51
detrites wrote: post #8

"If you’re a programmer and you’re curious to know what BERT fine-tuning looks like, my book offers an _example_. But 2018 was a long time ago. ChatGPT doesn’t rely on fine-tuned versions of BERT. The next section explains why." This paragraph unfortunately may be misinterpreted to mean the authors book is from 2018 and out of date. Actually, his book was published a few months ago. The author here is referring to th…

Yeah I was misled by that at first too. I'll be picking it up, assuming that the book is as well written and clear and concise as that article.

I've just finished Chapter 1, and I would say it is as good as the article. One caveat is that while the book claims it can be understood by a person who can't program, I'd expect them to feel rather mystified during the many coding parts.

Even so, the surrounding text explains the code well enough it probably wouldn't impact a persons ability to understand the material being presented. It's not aimed at 5-year-olds but I'd say it's not aimed so much at the titles Engineers.

One thing I've appreciated is the presentation of raw data. Every time a new type of data is introduced, the book shows its structure. It's been much easier to get what's going on as a result. Hope the rest is as good as the first chapter.

Re: Understanding ChatGPT

#150

Post by [deleted] »

the_gipsy wrote: post #116
fauigerzigerk wrote: post #63

Earlier quoted context omitted.

>“It’s a glorified word predictor” is becoming increasingly maddening to read. Do tell— how can you prove humans are any different? One difference between humans and LLMs is that humans have a wide range of inputs and outputs beyond language. The claim that humans are word predictors is not something I would want to dispute. The claim that humans are nothing more than word predictors is obviously wrong though. When I…

But maybe the "I'm hungry" inner monologue is just word prediction, and this could be the most important thing about being human. Transforming some digestive nerve stimulus into a trigger (prompt?) for those words might not be important.

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