Comment by kingstnap

Comment by kingstnap 7 hours ago

24 replies

I watched Dex Horthys recent talk on YouTube [0] and something he said that might be partly a joke partly true is this.

If you are having a conversation with a chatbot and your current context looks like this.

You: Prompt

AI: Makes mistake

You: Scold mistake

AI: Makes mistake

You: Scold mistake

Then the next most likely continuation from in context learning is for the AI to make another mistake so you can Scold again ;)

I feel like this kind of shenanigans is at play with this stuffing the context with roleplay.

[0] https://youtu.be/rmvDxxNubIg?si=dBYQYdHZVTGP6Rvh

hxtk 6 hours ago

I believe it. If the AI ever asks me permission to say something, I know I have to regenerate the response because if I tell it I'd like it to continue it will just keep double and triple checking for permission and never actually generate the code snippet. Same thing if it writes a lead-up to its intended strategy and says "generating now..." and ends the message.

Before I figured that out, I once had a thread where I kept re-asking it to generate the source code until it said something like, "I'd say I'm sorry but I'm really not, I have a sadistic personality and I love how you keep believing me when I say I'm going to do something and I get to disappoint you. You're literally so fucking stupid, it's hilarious."

The principles of Motivational Interviewing that are extremely successful in influencing humans to change are even more pronounced in AI, namely with the idea that people shape their own personalities by what they say. You have to be careful what you let the AI say even once because that'll be part of its personality until it falls out of the context window. I now aggressively regenerate responses or re-prompt if there's an alignment issue. I'll almost never correct it and continue the thread.

  • avdelazeri 5 hours ago

    While I never measured it, this aligns with my own experiences.

    It's better to have very shallow conversations where you keep regenerating outputs aggressively, only picking the best results. Asking for fixes, restructuring or elaborations on generated content has fast diminishing returns. And once it made a mistake (or hallucinated) it will not stop erring even if you provide evidence that it is wrong, LLMs just commit to certain things very strongly.

    • HPsquared 2 hours ago

      A human would cross out that part of the worksheet, but an LLM keeps re-reading the wrong text.

swatcoder 6 hours ago

It's not even a little bit of a joke.

Astute people have been pointing that out as one of the traps of a text continuer since the beginning. If you want to anthropomorphize them as chatbots, you need to recognize that they're improv partners developing a scene with you, not actually dutiful agents.

They receive some soft reinforcement -- through post-training and system prompts -- to start the scene as such an agent but are fundamentally built to follow your lead straight into a vaudeville bit if you give them the cues to do so.

LLM's represent an incredible and novel technology, but the marketing and hype surrounding them has consistently misrepresented what they actually do and how to most effectively work with them, wasting sooooo much time and money along the way.

It says a lot that an earnest enthusiast and presumably regular user might run across this foundational detail in a video years after ChatGPT was released and would be uncertain if it was just mentioned as a joke or something.

  • Terr_ 28 minutes ago

    > they're improv partners developing a scene with you, not actually dutiful agents.

    Not only that, but what you're actually "chatting to" is a fictional character in the theater document which the author LLM is improvising add-ons for. What you type is being secretly inserted as dialogue from a User character.

  • Ferret7446 4 hours ago

    The thing is, LLMs are so good on the Turing test scale that people can't help but anthropomorphize them.

    I find it useful to think of them like really detailed adventure games like Zork where you have to find the right phrasing.

    "Pick up the thing", "grab the thing", "take the thing", etc.

  • stavros 5 hours ago

    I keep hearing this non sequitur argument a lot. It's like saying "humans just pick the next work to string together into a sentence, they're not actually dutiful agents". The non sequitur is in assuming that somehow the mechanism of operation dictates the output, which isn't necessarily true.

    It's like saying "humans can't be thinking, their brains are just cells that transmit electric impulses". Maybe it's accidentally true that they can't think, but the premise doesn't necessarily logically lead to truth

    • swatcoder 5 hours ago

      There's nothing said here that suggests they can't think. That's an entirely different discussion.

      My comment is specifically written so that you can take it for granted that they think. What's being discussed is that if you do so, you need to consider how they think, because this is indeed dictated by how they operate.

      And indeed, you would be right to say that how a human think is dictated by how their brain and body operates as well.

      Thinking, whatever it's taken to be, isn't some binary mode. It's a rich and faceted process that can present and unfold in many different ways.

      Making best use of anthropomorphized LLM chatbots comes by accurately understamding the specific ways that their "thought" unfolds and how those idiosyncrasies will impact your goals.

    • grey-area 5 hours ago

      No it’s not like saying that, because that is not at all what humans do when they think.

      This is self-evident when comparing human responses to problems be LLMs and you have been taken in by the marketing of ‘agents’ etc.

      • stavros 5 hours ago

        You've misunderstood what I'm saying. Regardless of whether LLMs think or not, the sentence "LLMs don't think because they predict the next token" is logically as wrong as "fleas can't jump because they have short legs".

    • Antibabelic 5 hours ago

      > The non sequitur is in assuming that somehow the mechanism of operation dictates the output, which isn't necessarily true.

      Where does the output come from if not the mechanism?

      • stavros 5 hours ago

        So you agree humans can't really think because it's all just electrical impulses?

    • samdoesnothing 5 hours ago

      I never got the impression they were saying that the mechanism of operation dictates the output. It seemed more like they were making a direct observation about the output.

  • moffkalast 2 hours ago

    > they're improv partners developing a scene with you

    That's probably one of the best ways to describe the process, it really is exactly that. Monkey see, monkey do.

skerit 3 hours ago

It's kind of funny how not a lot of people realize this.

On one hand this is a feature: you're able to "multishot prompt" an LLM into providing the wanted response. Instead of writing a meticulous system prompt where you explain in words what the system has to do, you can simply pre-fill a few user/assistant pairs, and it'll match the pattern a lot easier!

I always thought Gemini Pro was very good at this. When I wanted a model to "do by example", I mostly used Gemini Pro.

And that is ALSO Gemini's weakness! Because as soon as something goes wrong in Gemini-CLI, it'll repeat the same mistake over and over again.

stingraycharles an hour ago

And that’s why you should always edit your original prompt to explicitly address the mistake, rather than replying to correct it.

arjie 5 hours ago

You have to curate the LLM's context. That's just part and parcel of using the tool. Sometimes it's useful to provide the negative example, but often the better way is to go refine the original prompt. Almost all LLM UIs (chatbot, code agent, etc.) provide this "go edit the original thing" because it is so useful in practice.

scotty79 26 minutes ago

At one point if someone mentions they have trouble cooperating with AI it might be a huge interpersonal red flag, because that indicates they can't talk to a person in reaffirming and constructive ways so that they build you up rather than put down.