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LLMs are steroids for your Dunning-Kruger

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Re: LLMs are steroids for your Dunning-Kruger

#271

Post by LeroyRaz »

yannyu wrote: post #246
ACCount37 wrote: post #130

Earlier quoted context omitted.

> But we already know the inner workings. Overconfident and wrong. No one understands how an LLM works. Some people just delude themselves into thinking that they do. Saying "I know how LLMs work because I read a paper about transformer architecture" is about as delusional as saying "I read a paper about transistors, and now I understand how Ryzen 9800X3D works". Maybe more so. It takes actual reverse engineering wor…

I never claimed we already know everything about LLMs. Knowing "everything about" anything these days is impossible given the complexity of our technology. Even antennae, a centuries old technology, is something we're still innovating on and don't completely understand in all domains. But that's a categorically different statement than "no one understands how an LLM works", because we absolutely do. You're spending a…

I think the person you are responding to is using a strange definition of "know."

I think they mean "do we understand how they process information to produce their outputs" (i.e., do we have an analytical description of the function they are trying to approximate).

You and I mean, we understand the training process that produces their behaviour (and this training process is mainly standard statistical modelling / ML).

In short, both sides are talking past each other.

Re: LLMs are steroids for your Dunning-Kruger

#272

Post by LeroyRaz »

Chabsff wrote: post #255
zahlman wrote: post #218

Earlier quoted context omitted.

My entire point here is that one can , in fact, reasonably claim to "understand" a system without being able to model its high level behaviors. It's not a mistake; it's disagreeing with you about what the word "understand" means.

For the sake of this conversation "understanding" implicitly means "understand enough about it to be unimpressed". This is what's being challenged: That you can discount LLMs as uninteresting because they are "just" probalistic inference machines. This completely underestimates just how far you can push the concept. Your pedantic definition of understand might be technically correct. But that's not what's being discu…

I'm not sure what you mean?

Saying we understand the training process of LLMs does not mean that LLMs are not super impressive. They are shining testiments to the power of statistical modelling / machine learning. Arbitrarily reclassifying them as something else is not useful. It is simply untrue.

There is nothing wrong with being impressed by statistics... You seem to be saying that statistics is interesting and there for to say that LLMs are statistics dismissed them. I think perhaps you are just implicitly biased against statistics! :p

Re: LLMs are steroids for your Dunning-Kruger

#273

Post by LeroyRaz »

ACCount37 wrote: post #138
parineum wrote: post #51

Earlier quoted context omitted.

I'm not sure what claim your disputing or making with this. What more are LLMs than statistical inference machines? I don't know that I'd assert that's all they are with confidence but all the configurations options I can play with during generation (Top K, Top P, Temperature, etc.) are all ways to _not_ select the most likely next token which leads me to believe that they are, in fact, just statistical inference mac…

What more are human brains than piles of wet meat? It's not an argument - it's a dismissal. It's boneheaded refusal to think on the matter in any depth, or consider any of the implications. The main reason to say "LLMs are just next token predictions" is to stop thinking about all the inconvenient things. Things like "how the fuck does training on piles of text make machines that can write new short stories" or "why…

I mean, yeah, statistics works. It's not that surprising that super amazing statistical modelling can approximate a distribution. Of course, thoughts, words, arguments are distributions, and with a powerful enough model you can simulate them.

None of this is surprising? Like, I think you just lack a good statistical intuition. The amazing thing is that we have these extremely capable models, and methods to learn them. That process is an active area of research (as is much of statistics), but it is just all statistics...

Re: LLMs are steroids for your Dunning-Kruger

#274

Post by LeroyRaz »

Chabsff wrote: post #256
zahlman wrote: post #186

Earlier quoted context omitted.

> What more are human brains than piles of wet meat? Calculation isn't what makes us special; that's down to things like consciousness, self-awareness and volition. > The main reason to say "LLMs are just next token predictions" is to stop thinking about all the inconvenient things. Things like... They do it by iteratively predicting the next token. Suppose the calculations to do a more detailed analysis were tractab…

> They do it by iteratively predicting the next token. You don't know that. It's how the llm presents, not how it does things. That's what I mean by it being the interface. There's ever only one word that comes out of your mouth at a time, but we don't conclude that humans only think one word at a time. Who's to say the machine doesn't plan out the full sentence and outputs just the next token? I don't know either fw…

Have you read the literature? Do you have a background in machine learning or statistics?

Yes. We know that LLMs can be trained by predicting the next token. This is a fact. You can look up the research papers, and open source training code.

I can't work it out, are you advocating a conspiracy theory that these models are trained with some elusive secret and that the researchers are lying to you?

Being trained by predicting one token at a time is also not a criticism??! It is just a factually correct description...

Re: LLMs are steroids for your Dunning-Kruger

#275

Post by LeroyRaz »

AndrewKemendo wrote: post #15

Humans broadly have a tenuous grasp of “reality” and “truth.” Propagandists, spies and marketers know what philosophers of mind prove all too well: most humans do not perceive or interact with reality as it is, rather their perception of it as it contributes or contradicts their desired future. Provide a person confidence in their opinion and they will not challenge it, as that would risk the reward of lend you live…

Hacker News readers, and especially commenters, are number 1!

Re: LLMs are steroids for your Dunning-Kruger

#276

Post by GMoromisato »

hathawsh wrote: post #94
GMoromisato wrote: post #44

Speaking of uncertainty, I wish more people would accept their uncertainty with regards to the future of LLMs rather than dash off yet another cocksure article about how LLMs are {X}, and therefore {completely useless}|{world-changing}. Quantity has a quality of its own. The first chess engine to beat Gary Kasparov wasn't fundamentally different than earlier ones--it just had a lot more compute power. The original Go…

Most of HN has probably seen this gem about "thinking meat", but in case you haven't: https://www.mit.edu/people/dpolicar/writing/prose/text/think...

Yes, thanks for the link.

I just re-read it a few weeks ago and it was still fresh in my mind!

Re: LLMs are steroids for your Dunning-Kruger

#277

Post by jalapenos »

Insanity wrote: post #11
sho_hn wrote: post #4

I'm not sure this is something I really worry about. Whenever I use an LLM I feel dumber, not smarter; there's a sensation of relying on a crutch instead of having done the due diligence of learning something myself. I'm less confident in the knowledge and less likely to present it as such. Is anyone really cocksure on the basis of LLM received knowledge? > As I ChatGPT user I notice that I’m often left with a sense…

I remember back when I was in secondary school, something commonly heard was "Don't just trust wikipedia, check it's resources, because it's crowdsourced and can be wrong". Now, almost 2 decades later, I rarely hear this stance and I see people relying on wikipedia as an authoritative source of truth. i.e, linking to wikipedia instead of the underlying sources. In the same sense, I can see that "Don't trust LLMs" wil…

Problem is they also included newspapers in authoritative sources - except foreign ones that is - and Wikipedia at least has some kind of peer review process.

It's genuinely as authoritative as most other things called authoritative.

Re: LLMs are steroids for your Dunning-Kruger

#278

Post by jalapenos »

jermaustin1 wrote: post #102
miningape wrote: post #52

Earlier quoted context omitted.

> "Don't just trust wikipedia, check it's resources, because it's crowdsourced and can be wrong" This comes from decades of teachers misremembering what the rule was, and eventually it morphed into the Wikipedia specific form we see today - the actual rule is that you cannot cite an encyclopaedia in an academic paper. full stop. Wikipedia is an encyclopaedia and therefore should not be cited. Wikipedia is the only en…

I remember all of our encyclopedias being decades out of date growing up. My parents bought a set of Encyclopedia Brittanica in 1976 or something like that, so by the time I was reading the Encyclopedia for research on papers in the late 90s and early 00s, it was without a doubt less factual than even the earliest incarnation of Wikipedia was. Either way, you are correct, we weren't allowed to cite any encyclopedia,…

> we weren't allowed to even look at it (blocked from school computers)

Same thing happened with ChatGPT - teachers hate competition

Re: LLMs are steroids for your Dunning-Kruger

#279

Post by yannyu »

LeroyRaz wrote: post #271
yannyu wrote: post #246

Earlier quoted context omitted.

I never claimed we already know everything about LLMs. Knowing "everything about" anything these days is impossible given the complexity of our technology. Even antennae, a centuries old technology, is something we're still innovating on and don't completely understand in all domains. But that's a categorically different statement than "no one understands how an LLM works", because we absolutely do. You're spending a…

I think the person you are responding to is using a strange definition of "know." I think they mean "do we understand how they process information to produce their outputs" (i.e., do we have an analytical description of the function they are trying to approximate). You and I mean, we understand the training process that produces their behaviour (and this training process is mainly standard statistical modelling / ML)…

I agree. The two of us are talking past each other, and I wonder if it's because there's a certain strain of thought around LLMs that believes that epistemological questions and technology that we don't fully understand are somehow unique to computer science problems.

Questions about the nature of knowledge (epistemology and other philosophical/cognitive studies) in humans are still unsolved to this day, and frankly may never be fully understood. I'm not saying this makes LLM automatically similar to human intelligence, but there are plenty of behaviors, instincts, and knowledge across many kinds of objects that we don't fully understand the origin of. LLMs aren't qualitatively different in this way.

There are many technologies that we used that we didn't fully understand at the time, even iterating and improving on those designs without having a strong theory behind them. Only later did we develop the theoretical frameworks that explain how those things work. Much like we're now researching the underpinnings of how LLMs work to develop more robust theories around them.

I'm genuinely trying to engage in a conversation and understand where this person is coming from and what they think is so unique about this moment and this technology. I understand the technological feat and I think it's a huge step forward, but I don't understand the mysticism that has emerged around it.

Re: LLMs are steroids for your Dunning-Kruger

#280

Post by svieira »

ACCount37 wrote: post #114
svieira wrote: post #58

Earlier quoted context omitted.

> How can meat think? Some of us used to think that meat spontaneously generated flies. Maybe someday we'll (re-)learn that meat doesn't spontaneously generate thought either?

I don't give much merit to ideas that demand the existence of Magic Fairy Dust. And especially not now. Not when LLMs can already do pretty much anything that a human can - and some of those things they can even do well .

Given that everything the LLM can do it learned from human descriptions of the space ... one would have to posit a very inefficient language for that model not to do something with those billions of parameters. But when you fly because of a bunch of balloons sprinkled with magic fairy dust are pulling you up, the magic fairy dust is still at work.
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