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LLMs are steroids for your Dunning-Kruger

bytesauna.com

181–190 of 308 posts

Re: LLMs are steroids for your Dunning-Kruger

#181
post #57

I've seen this! Following some Math and Physics subreddits it's a regular occurrence for a new submitter to come in and post some 40 pages of incomprehensible bullshit and claim that they developed a unifying theory of physics with ChatGPT and that ChatGPT has told them it's a breakthrough in the field. Of course that used to happen regularly before LLMs but not nearly as often.

Including the former CEO of Uber. I’m somewhat curious what these people even think they’ve discovered, what outstanding problem they think they’ve actually solved… but I’m not curious enough to actually dig through their slop.

https://gizmodo.com/billionaires-convince-themselves-ai-is-c...

Re: LLMs are steroids for your Dunning-Kruger

#182
post #30

Earlier quoted context omitted.

Wikipedia is usually close enough and most users don't require perfection for their "facts" Ive noticed things like gemini summaries on Google searches are also generally close enough.

Close enough only counts in horseshoes and hand grenades

And most human communication

Re: LLMs are steroids for your Dunning-Kruger

#183

LLMs, kind of like Bill Bryson's books, are great at presenting "information" that seems completely plausible, authoritative, and convincing to the reader. But when you actually do know the truth about a subject, you realize how completely full of crap they too often are. And somehow after being given a patently counterfactual response to one query, we just blindly continue to take their responses to other queries as…

I don't quite disagree but this comparison is typically unfair, because when you really know about a subject you tend to ask way more difficult questions than about other subjects, so of course the LLMs are gonna struggle more. If you ask really basic questions they will regurgitate well known bachelor-level knowledge and look good. What do I know about biology anyway? about silos for grain storage? any passable answ…

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Re: LLMs are steroids for your Dunning-Kruger

#184
post #103

Earlier quoted context omitted.

> Then why not say "they are just computer programs"? LLMs are probabilistic or non-deterministic computer programs, plenty of people say this. That is not much different than saying "LLMs are probabilistic next-token prediction based on current context". > I think the reason people don't say that is because they want to say "I already understand what they are, and I'm not impressed and it's nothing new". But what th…

> 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…

> 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.

Which is to say, not delusional at all.

Or else we have to accept that basically hardly anyone "understands" anything. You set an unrealistic standard.

Beginners play abstract board games terribly. We don't say that this means they "don't understand" the game until they become experts; nor do we say that the experts "haven't understood" the game because it isn't strongly solved. Knowing the rules, consistently making legal moves and perhaps having some basic tactical ideas is generally considered sufficient.

Similarly, people who took the SICP course and didn't emerge thoroughly confused can reasonably be said to "understand how to program". They don't have to create MLOC-sized systems to prove it.

> It takes actual reverse engineering work to figure out how LLMs can do small bits and tiny slivers of what they do. And here you are - claiming that we actually already know everything there is to know about them.

No; it's a dismissal of the relevance of doing more detailed analysis, specifically to the question of what "understanding" entails.

The fact that a large pile of "transformers" is capable of producing the results we see now, may be surprising; and we may lack the mental resources needed to trace through a given calculation and ascribe aspects of the result to specific outputs from specific parts of the computation. But that just means it's a massive computation. It doesn't fundamentally change how that computation works, and doesn't negate the "understanding" thereof.

Re: LLMs are steroids for your Dunning-Kruger

#185

Earlier quoted context omitted.

It makes me really sad how Google pushes this technology that is simply flat out wrong sometimes. I forgot what exactly I searched for, but I searched for a color model that Krita supports hoping to get the online documentation as the first result and the under several Youtube thumbnails the AI overview was telling me that Krita doesn't support that color model and you need a plugin for that. Under the AI overview wa…

The AI is also indiscriminate with what "sources" it chooses. Even deep research mode in gemini. You can go through and look at the websites it checked, and it's 80% blogspam with no other sources cited on said blog. When I'm manually doing a Google search, I'm not just randomly picking the first few links I'm deliberately filtering for credible domains or articles, not just picking whatever random marketing blog SEO…

It's trained on them, yes. But is it trained to prefer them as sources when doing web search?

The distinction is rather important.

We have a lot of data that teaches LLMs useful knowledge, but data that teaches LLMs complex and useful behaviors? Far less represented in the natural datasets.

It's why we have to do SFT, RLHF and RLVR. It's why AI contamination in real world text datasets, counterintuitively, improves downstream AI performance.

Re: LLMs are steroids for your Dunning-Kruger

#186

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…

> 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 tractable. Why should we expect the result to be any more insightful? It would not make the computer conscious, self-aware or motivated. For the same reason that conventional programs do not.

Re: LLMs are steroids for your Dunning-Kruger

#187

Earlier quoted context omitted.

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…

> "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…

That's why you should cite Grokipedia instead /s

Re: LLMs are steroids for your Dunning-Kruger

#188
> LLMs should not be seen as knowledge engines but as confidence engines.

The thing I like best about LLM is when I ask question about some technical problem, and it tells that it is a KNOWN problem. It thus gives me confiidence that I don't need to spend time) to look for solution where there is no good soloution. Just go around it somehow. It let's me know I'm not the only person with this problem. And that way it gives me confidence that I'm not stupid, the problem is a real problem.

As an example I was working with WebStorm and tried to find a way to make the Threads-tab the default tab shown when debugger opens. AI told me there is no way it knows about. Good, problem solved, solved by finding out there is no solution.

Re: LLMs are steroids for your Dunning-Kruger

#189

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…

> 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. Which is to say, not delusional at all. Or else we have to accept that basically hardly anyone "understands" anything . You set an unrealistic standard. Beginners play abstract board games terribly. We do…

Understanding a transistor is an incredibly small part of how Ryzen 9800X3D does what it does.

Is it a foundational part? Yes. But if you have it and nothing else, that adds up to knowing almost nothing about how the whole CPU works. And you could come to understand much more than that without ever learning what a "transistor" even is.

Understanding low level foundations does not automatically confer the understanding of high level behaviors! I wish I could make THAT into a nail, and drive it into people's skulls, because I keep seeing people who INSIST on making this mistake over and over and over and over and over again.

Re: LLMs are steroids for your Dunning-Kruger

#190
post #89

Earlier quoted context omitted.

The original rule when I was a lad (when wikipedia was a baby) was, "don't trust stuff on the internet, especially Wikipedia where people can change it at will." Today they might have better trust for Wikipedia-- and I know I use it as a source of truth for a lot of things-- but back in my day teachers were of the opinion that it couldn't be trusted. This was for like middle and high school, not college or university…

There was a period of time where Wikipedia was more scrutinized than print encyclopedias because people did not understand the power of having 1000s of experts and the occasional non-experts editing an entry for free instead of underpaying one sudo-expert. They couldn't comprehend how an open source encyclopedia would even work or trust that humans could effectively collaborate on the task. They imagined that 1000s o…

> the power of having 1000s of experts and the occasional non-experts editing an entry

When Wikipedia was founded, it was much easier to change articles without notice. There may not have been 1000s of experts at the time, like there are today. There's also other things that Wikipedia does to ensure articles are accurate today that they may not have done or been able to do decades ago.

I am not making a judgment of Wikipedia, I use it quite a bit, I am just stating that it wasn't trusted when it first came out specifically because it could be changed by anyone. No one understood it then, but today I think people understand that it's probably as trustworthy or moreso than a traditional encyclopedia is/was.

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