3 ms·

So the easiest way to generate a bit more novelty is to ask GPT to generate 10 or 20 examples, and to explicitly direct it that they should run a full gamut --

So the easiest way to generate a bit more novelty is to ask GPT to generate 10 or 20 examples, and to explicitly direct it that they should run a full gamut -- in this case I'd say "Try to cover the whole spectrum of creativity -- some should be straightforward genre puzzles while some should be so outright goofy that they'd be hard to play in real life." Giving GPT that prompt, the first example it came up with was kind of middling ("The players encounter a circle of stones that hum when approached. Touching them randomly will cause a loud dissonant noise that could attract monsters. Players must replicate a specific melody by touching the stones in the correct order"), some were bad (a maze of mirrors, a sphinx with a riddle, a puzzle box that poisons you if you try to force it), some were actually genuinely fun-sounding (a door which shocks you if you try to open it and then mocks and laughs at you: you have to tell it a joke to get it to laugh enough that it opens on its own; particularly bad jokes will cause it to summon an imp to attack you). Some were bad in the way GPT presented but I could maybe have fun with (a garden of emotion-sensitive plants, thorny if you're angry or helpful if you're gentle; a fountain-statue of a woman weeping real water for tears, the fountain itself is inhabited by a water elemental that lashes out to protect her from being touched while she grieves -- but a token or an apology can still the tears and open her clasped hands to reveal a treasure). The one that I would be most likely to use was "A pool of water that reflects the players’ true selves. Touching the water causes it to ripple and distort the reflection, summoning shadowy duplicates. By speaking a truth about themselves, players can calm the water and reveal a hidden item. Common mistakes include lying, which causes the water to become turbulent, and trying to take the item without calming the water, which summons the duplicates." So like you can get it to have a 5-10% success rate, which can be helpful if you're looking for a random new idea. This reminds me vaguely of when I was a teen writing fanfics in the late 90s and was just learning JavaScript -- I wrote a lot of things that would just choose random characters, random problems for them to solve, random stumbling blocks, random keys-to-solve-the-problem. Combinatorial explosion. Then you'd just click "generate" and you'd get a mediocre plot idea. But you generate 20-30 times or more and you'd get one that kinda sat with you, "Hm, Cloud Strife and Fox McCloud are stuck in intergalactic prison and need to break out, huh, that could be fun, like they're both trying to outplay the other as the silent action hero" and then you could go and write it out and see if it was any good. The difference is that the database of crappy ideas is already built into GPT, you just need to get it to make you some.

stickfigure 2y ago
> (a door which shocks you if you try to open it and then mocks and laughs at you: you have to tell it a joke to get it to laugh enough that it opens on its own; particularly bad jokes will cause it to summon an imp to attack you) That's pretty great! And way more fun than the parent poster's puzzle (sorry). I think the AIs are winning this one.
- throwup238 2y ago
  Small changes to the prompt like that have a huge impact on the solution space LLMs generate which is why “prompt engineering” plays any significance. This was rather obvious IMO from the beginning of GPT4 where you could tell it to write in the style of Hunter S Thompson or Charles Bukowski or something which drastically changes the tone and style. Combining them to get the exact language you want can be a painstaking process but LLMs are definitely capable of any kind of style.
YurgenJurgensen 2y ago
So what you need to do is take a system that’s already computationally inefficient, and make it 20 times less efficient? Who’s paying for this? This also sounds like a way to blow out context windows.
- unoti 2y ago
  Regarding cost, doing something like this would be fractions of a penny. Obviously, the person doing the API calls is either paying for it, or they're paying for the electricity if they do it on their machine. But the cost is ultra negligible; certainly cheaper than it would be on Mechanical Turk or Fiverr. In fact so much cheaper that economically it wouldn't be feasible or worth the effort to try outsourcing it ordinarily. This is part of the game changer nature of AI. Regarding blowing out context windows, yes, probably, but this is what loops and code are for. Think of implementing a system like a guided seminar that steps a person doing this work through it step by step, and giving them time and opportunity to iterate on and improve the product. For example, with making up the D&D puzzles. Ask a college educated human to do this. You will find there's things you like and don't like about their results. Tell them more about what you're looking for, what you like, and what you don't like. Give them examples of what you like and don't like. Take notes on the things you discuss with them until you figure out a way to express how to coax out of a fresh person new to this topic how to give you what you want. When working with the person, work out a process where they have rough drafts, and you walk them through how to select the best items and give them pointers on how to improve on them. Write up a written process for how to do this. Maybe there are multiple phases in this process, and things go through multiple revisions to get to quality material. Now do the same thing with the LLM, and you have yourself a good system. Same thing goes for writing stories, which elsewhere in these threads people say LLM's are terrible at. Sit a human down and tell them to give you a story, and I promise you will receive terrible results or outright copying. Instead, give your humans some guidelines. Like start with the idea that in the end our hero is going to be a particular way with particular strengths they need to conquer the central challenge. But in the beginning, they are the complete opposite of that thing. What is the central challenge, and what are the characteristics they need to conquer it? In what ways will the main character be the opposite of that at the beginning of the story? Then we put the character through hell in various ways over the course of the story to enact those changes in their character that they need to win in the end. For each of these sentences/phases above, make things that explain the ideas more fully, and make a process to iterate on these things, possibly with multiple different prompts and loops at every phase. This kind of approach more closely resembles what many real novelists do, iterating on ideas, often in the back of their mind or subconsciously, over hours or years of rumination with or without written outlines and notes. Maybe randomly select 2 things from movietropes.com and throw those in there saying incorporate these ideas. Experiment, iterate, see what works and what doesn't. People need to give LLM's the domain knowledge and capability of rumination to succeed in so many of these domains, rather than just asking "write me a novel" and being disappointed. Or asking "write me a puzzle my D&D group will enjoy" without going through these extra steps that are implicit/intuitive for what experienced subject matter experts do. Source: I write AI products for a living with many things in production delivering real business value at scale every day. It's not all hype, it just takes a while to implement.

stickfigure 2y ago

> (a door which shocks you if you try to open it and then mocks and laughs at you: you have to tell it a joke to get it to laugh enough that it opens on its own; particularly bad jokes will cause it to summon an imp to attack you) That's pretty great! And way more fun than the parent poster's puzzle (sorry). I think the AIs are winning this one.

throwup238 2y ago
Small changes to the prompt like that have a huge impact on the solution space LLMs generate which is why “prompt engineering” plays any significance. This was rather obvious IMO from the beginning of GPT4 where you could tell it to write in the style of Hunter S Thompson or Charles Bukowski or something which drastically changes the tone and style. Combining them to get the exact language you want can be a painstaking process but LLMs are definitely capable of any kind of style.

YurgenJurgensen 2y ago

So what you need to do is take a system that’s already computationally inefficient, and make it 20 times less efficient? Who’s paying for this? This also sounds like a way to blow out context windows.

unoti 2y ago
Regarding cost, doing something like this would be fractions of a penny. Obviously, the person doing the API calls is either paying for it, or they're paying for the electricity if they do it on their machine. But the cost is ultra negligible; certainly cheaper than it would be on Mechanical Turk or Fiverr. In fact so much cheaper that economically it wouldn't be feasible or worth the effort to try outsourcing it ordinarily. This is part of the game changer nature of AI. Regarding blowing out context windows, yes, probably, but this is what loops and code are for. Think of implementing a system like a guided seminar that steps a person doing this work through it step by step, and giving them time and opportunity to iterate on and improve the product. For example, with making up the D&D puzzles. Ask a college educated human to do this. You will find there's things you like and don't like about their results. Tell them more about what you're looking for, what you like, and what you don't like. Give them examples of what you like and don't like. Take notes on the things you discuss with them until you figure out a way to express how to coax out of a fresh person new to this topic how to give you what you want. When working with the person, work out a process where they have rough drafts, and you walk them through how to select the best items and give them pointers on how to improve on them. Write up a written process for how to do this. Maybe there are multiple phases in this process, and things go through multiple revisions to get to quality material. Now do the same thing with the LLM, and you have yourself a good system. Same thing goes for writing stories, which elsewhere in these threads people say LLM's are terrible at. Sit a human down and tell them to give you a story, and I promise you will receive terrible results or outright copying. Instead, give your humans some guidelines. Like start with the idea that in the end our hero is going to be a particular way with particular strengths they need to conquer the central challenge. But in the beginning, they are the complete opposite of that thing. What is the central challenge, and what are the characteristics they need to conquer it? In what ways will the main character be the opposite of that at the beginning of the story? Then we put the character through hell in various ways over the course of the story to enact those changes in their character that they need to win in the end. For each of these sentences/phases above, make things that explain the ideas more fully, and make a process to iterate on these things, possibly with multiple different prompts and loops at every phase. This kind of approach more closely resembles what many real novelists do, iterating on ideas, often in the back of their mind or subconsciously, over hours or years of rumination with or without written outlines and notes. Maybe randomly select 2 things from movietropes.com and throw those in there saying incorporate these ideas. Experiment, iterate, see what works and what doesn't. People need to give LLM's the domain knowledge and capability of rumination to succeed in so many of these domains, rather than just asking "write me a novel" and being disappointed. Or asking "write me a puzzle my D&D group will enjoy" without going through these extra steps that are implicit/intuitive for what experienced subject matter experts do. Source: I write AI products for a living with many things in production delivering real business value at scale every day. It's not all hype, it just takes a while to implement.