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The "confident idiot" problem: Why AI needs hard rules, not vibe checks

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131–140 of 399 posts

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#131

The thing that bothers me the most about LLMs is how they never seem to understand "the flow" of an actual conversation between humans. When I ask a person something, I expect them to give me a short reply which includes another question/asks for details/clarification. A conversation is thus an ongoing "dance" where the questioner and answerer gradually arrive to the same shared meaning. LLMs don't do this. Instead,…

I never expected LLMs to be like an actual conversation between humans. The model is in some respects more capable and in some respects more limited than a human. I mean, one could strive for an exact replica of a human -- but for what purpose? The whole thing is a huge association machine. It is a surealistic inspiration generator for me. This is how it works at the moment, until the next break through ...

Clarifying ambiguity in questions before dedicating more resources to search and reasoning about the answer seems both essential and almost trivial to elicit via RLHF.

I'd be surprised if you can't already make current models behave like that with an appropriate system prompt.

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#132

Earlier quoted context omitted.

I never expected LLMs to be like an actual conversation between humans. The model is in some respects more capable and in some respects more limited than a human. I mean, one could strive for an exact replica of a human -- but for what purpose? The whole thing is a huge association machine. It is a surealistic inspiration generator for me. This is how it works at the moment, until the next break through ...

> but for what purpose? I recently introduced a non-technical person to Claude Code, and this non-human behavior was a big sticking point. They tried to talk to Claude similar as to a human, presenting it one piece of information at a time. With humans this is generally beneficial, and they will either nod for you to continue or ask clarifying questions. With Claude this does not work well, you have to infodump as mu…

also, this is what chat-style interfaces encourage. Anything where the "enter" key sends the message instead of creating a paragraph block is just hell.

I'm prompting Gemini, and I write:

I have the following code, can you help me analyze it?

but Gemnini is already generating output, usually saying "I'm waiting for you to enter the code"

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#134
post #124

The thing that bothers me the most about LLMs is how they never seem to understand "the flow" of an actual conversation between humans. When I ask a person something, I expect them to give me a short reply which includes another question/asks for details/clarification. A conversation is thus an ongoing "dance" where the questioner and answerer gradually arrive to the same shared meaning. LLMs don't do this. Instead,…

Training data is quite literally weighted this way - long responses on Reddit have lots of tokens, and brief responses don't get counted nearly as much. The same goes for "rules" - you train an LLM with trillions of tokens and try to regulate its behavior with thousands. If you think of a person in high school, grading and feedback is a much higher percentage of the training.

Not to mention that Reddit users seek "confident idiots". Look at where the thoughtful questions that you'd expect to hear in a human social setting end up (hint: Downvoted until they disappear). Users on Reddit don't want to have to answer questions. They want to read the long responses that they can then nitpick. LLMs have no doubt picked up on that in the way they are trained.

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#135

The thing that bothers me the most about LLMs is how they never seem to understand "the flow" of an actual conversation between humans. When I ask a person something, I expect them to give me a short reply which includes another question/asks for details/clarification. A conversation is thus an ongoing "dance" where the questioner and answerer gradually arrive to the same shared meaning. LLMs don't do this. Instead,…

If you're paying per token then there is a big business incentive for the counterparty to burn tokens as much as possible.

As long as there's no moat (and arguably current LLM inference APIs are far from having one), it arguably doesn't really matter what users pay by.

The only thing I care about are whether the answer helps me out and how much I paid for it, whether it took the model a million tokens or one to get to it.

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#136

Confident idiot: I’m exploring using LLM for diagram creation. I’ve found after about 3 prompts to edit an image with Gemini, it will respond randomly with an entirely new image. Another quirk is it will respond “here’s the image with those edits” with no edits made. It’s like a toaster that will catch on fire every eighth or ninth time. I am not sure how to mitigate this behavior. I think maybe an LLM as a judge ste…

Whats your thoughts on the diagram as code movement? I'd prefer to have an LLM utilize those as it can atleast drive some determinism through it rather than deal with the slippery layer that is prompt control for visual LLMs.

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#137

The thing that bothers me the most about LLMs is how they never seem to understand "the flow" of an actual conversation between humans. When I ask a person something, I expect them to give me a short reply which includes another question/asks for details/clarification. A conversation is thus an ongoing "dance" where the questioner and answerer gradually arrive to the same shared meaning. LLMs don't do this. Instead,…

This drives me nuts when trying to bounce an architecture or coding solution idea off an LLM. A human would answer with something like "what if you split up the responsibility and had X service or Y whatever". No matter how many times you tell the LLM not to return code, it returns code. Like it can't think or reason about something without writing it out first.

I have architectural discussions all the time with coding agents.

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#138
post #116

We are trying to fix probability with more probability. That is a losing game. Thanks for pointing out the elephant in the room with LLMs. The basic design is non-deterministic. Trying to extract "facts" or "truth" or "accuracy" is an exercise in futility.

> The basic design is non-deterministic Is it? I thought an LLM was deterministic provided you run the exact same query on exact same hardware at a temperature of 0.

Not quite then as well, since a lot is typically executed in parallel and the implementation details of most number representations make them sensitive to the order of operations.

Given how much number crunching is at the heart of LLMs, these small differences add up.

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#139
post #104

Earlier quoted context omitted.

> I think they are much smarter than that. Or will be soon. It's not a matter of how smart they are (or appear), or how much smarter they may become - this is just the fundamental nature of Transformer-based LLMs and how they are trained. The sycophantic personality is mostly unrelated to this. Maybe it's part human preference (conferred via RLHF training), but the "You're asbolutely right! (I was wrong)" is clearly…

Sorry, double reply, I reread your comment and realised you probably know what you're talking about. Yeah, at its heart it's basically text compression. But the best way to compression, say, Wikipedia would be to know how the world works, at least according to the authors. As the recent popular "bag of words" post says: > Here’s one way to think about it: if there had been enough text to train an LLM in 1600, would i…

> So it needs to know facts, albeit the currently accepted ones. Knowing the facts is a good way to compression data.

It's not a compression engine - it's just a statistical predictor.

Would it do better if it was incentivized to compress (i.e training loss rewarded compression as well as penalizing next-word errors)? I doubt it would make a lot of difference - presumably it'd end up throwing away the less frequently occurring "outlier" data in favor of keeping what was more common, but that would result in it throwing away the rare expert opinion in favor of retaining the incorrect vox pop.

Re: The "confident idiot" problem: Why AI needs hard rules, not vibe checks

#140
LLMs are text model, not world models and that is the root cause of the problem. If you and I would be discussing furniture and for some reason you had assumed the furniture to be glued to the ceiling instead of standing on the floor (contrived example) then it would most likely only take one correction based on your actual experience that you are probably on the wrong track. An LLM will happily re-introduce that error a few ping-pongs later and re-establish the track it was on before because that apparently is some kind of attractor.

Not having a world model is a massive disadvantage when dealing with facts, the facts are supposed to re-inforce each other, if you allow even a single fact that is nonsense then you can very confidently deviate into what at best would be misguided science fiction, and at worst is going to end up being used as a basis to build an edifice on that simply has no support.

Facts are contagious: they work just like foundation stones, if you allow incorrect facts to become a part of your foundation you will be producing nonsense. This is my main gripe with AI and it is - funny enough - also my main gripe with some mass human activities.

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