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LLMs are not suitable for brainstorming

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Re: LLMs are not suitable for brainstorming

#61

Post by lanstin »

blackle wrote: post #27
nequo wrote: post #22

Earlier quoted context omitted.

Setting the temperature to a higher value would emulate this, wouldn't it? Then the model would be more willing to deviate from the most likely next token.

Increasing temperature just makes more uncommon tokens more likely to appear. This can include both uncommon ideas and uncommon spelling and grammatical mistakes. It also won't make ideas that the LLM isn't capable of thinking appear, unless you crank the temperature way up and get lucky (like monkeys on typewriters lucky)

That is also true for creative people. Generating interesting ideas is one thing then filtering out impractical or unaesthetic ideas is also needed.

Re: LLMs are not suitable for brainstorming

#62

Post by refulgentis »

hobobaggins wrote: post #49
dahart wrote: post #12

> The reason [LLMs are not a good tool to do truly effective brainstorming] is LLMs are trained to follow existing patterns in the human-produced corpus, and not natively taught to “brainstorm”. The problem with this argument is that people do the same thing, we’re not that great at brainstorming either. When we brainstorm in groups, we’re just bringing multiple points of view together. The more data LLMs are trained…

> people do the same thing You're right, most people do that, but that's because they haven't trained themselves to be inventors. This is a skill that definitely needs to be developed more, but finding truly creative (and sometimes backwards-seeming) solutions can sometimes mean thinking about problems in a completely different way. However, all LLM's do this. That's one of the points of the article.

There was an actual peer-reviewed article from an institution yesterday showing, numerically, robustly, human evaluated, that LLMs are better at creative thinking than humans.

I don't think handwaving about exclusively outputting training data and random punditry via article really holds up here.

It's wrong for so many reasons, from the training data having more perspectives, to the "Fat Tony" test, empirically, we can go make it output novel combinations right now, to the CS test, we can have it emulate arbitrary Turing machines.

Re: LLMs are not suitable for brainstorming

#63

Post by bawolff »

chefandy wrote: post #32
bawolff wrote: post #21

> What’s worse is when we ask topics that don’t have consensus currently, the LLMs won’t behave in a more creative and independent way (as we hoped), but more susceptible to issues like hallucination. I mean, what is the difference between creativity and hallucination (honest question)? --- Maybe this means AI would be better at the opposite - after you brainstorm creative out there ideas, AI can tell you if they hav…

> I mean, what is the difference between creativity and hallucination (honest question)? Well, creative problem solving involves getting new ideas and perspectives by creating novel associations between things we know. Hallucinations are creating things we "know" because they sound like they could be right and basing "ideas" on them. In short, hallucinations are bullshit. Totally open creative problem solving isn't a…

Its not like humans always have good creative output. A lot of human creative output is essentially unworkable bullshit that gets discarded quite quickly.

I'm not saying llms are good at creativity (i certainly don't think they are) but i kind of feel like its a difference in quality not kind.

Like if you asked me to describe what it means for a human to be creative, i would probably write something quite similar to what you wrote above.

Re: LLMs are not suitable for brainstorming

#64

Post by jhbadger »

hobobaggins wrote: post #47
jhbadger wrote: post #40

Earlier quoted context omitted.

Nothing is really original. That's why you can make finite lists of the possible plots of books and movies. It's why TVtropes is a thing. Everything is just a mashup of things before.

Ah, yes, Everything that can be invented has been invented. - apocryphally attributed to Charles H. Duell, Commissioner of US Patent Office way back in 1889. This is a myth. Just because you don't really see blinding insight every day doesn't mean it doesn't exist (and it's more spectacular when you do see it!) Another reason that this seems to happen is that innovation and invention tend to happen in more esoteric a…

I happen to actually be a a computational biologist whose work could be considered "esoteric and technical" and whose papers are only fully understood by others in my field. But the fact is every paper of mine (and everybody else's) has 50 to 100 references. Because research is pretty much just reusing existing knowledge in the papers cited. The main source of "innovation", if it can be called that, is taking an idea from another field and applying it to your own. The idea of a scientist or inventor who comes up with an idea completely out the blue with no context is common in fiction, but that isn't how it works in reality.

Re: LLMs are not suitable for brainstorming

#65

Post by labrador »

behringer wrote: post #39
labrador wrote: post #19

Counterpoint: LLMs are very suitable for brainstorming if prompted appropriately LLMs are going to give you the consensus reality (average opinion? average facts?) but you can easily steer it into offbeat, controversial and esoteric areas of it's training with the right prompts

I spent a good long while trying to come up with novel video-game game play ideas, exactly what one would call "brainstorming" for ideas, and quite frankly it was pretty awful. ChatGPT more or less it converged on simply taking the current subject, adding a generic gameplay element to it and outputting it. It took half the ideas being thrown at it and included a rhythm mechanic... That's not that interesting, and I j…

That's a good point I forgot to mention. It really depends on your subject matter.

I put a clip up supporting why I think LLMs are good for brainstorming from Marc Andreeson about this topic in case your interested

"Marc Andreessen says with the right prompting, you can unlock the latent super genius in AI models"

https://www.youtube.com/watch?v=N2yN4IG8UYA

And here's my comment on another site to a pro novelist who suddenly discovered Claude wrote like a genius who posits that Anthropic deliberatly cripples Claude's writing ability because they don't want to scare writers suddenly, they want to ease them into it

I disagree. Your supernatural scenes triggered words an analysis from higher quality writers and commenters in the training data. If you were writing about bass fishing it would likely not impress you with it's writing. You can try something like this as an experiment. In other words it's good at some writing and bad at others, depending on the training data. I'd love to be proven wrong, like a gripping story about bass fishing might be interesting.

Re: LLMs are not suitable for brainstorming

#66

Post by chefandy »

bawolff wrote: post #63
chefandy wrote: post #32

Earlier quoted context omitted.

> I mean, what is the difference between creativity and hallucination (honest question)? Well, creative problem solving involves getting new ideas and perspectives by creating novel associations between things we know. Hallucinations are creating things we "know" because they sound like they could be right and basing "ideas" on them. In short, hallucinations are bullshit. Totally open creative problem solving isn't a…

Its not like humans always have good creative output. A lot of human creative output is essentially unworkable bullshit that gets discarded quite quickly. I'm not saying llms are good at creativity (i certainly don't think they are) but i kind of feel like its a difference in quality not kind. Like if you asked me to describe what it means for a human to be creative, i would probably write something quite similar to…

The main difference for my use case is what's usable about off-the-mark creative output to those who engage with it. With an LLM's hallucination, bullshit was made, bullshit was received, and that's that. If you figure out it's bullshit, the only thing you've likely gained from the exercise is having one less piece of bullshit to consider.

With humans creatively solving problems, what they say isn't 'output'-- it's externalizing a reasoning process. Being off-the-mark about something is a beneficial part of defining the bounds of an unknown solution because it's based on reality. It's a tangible idea that can be reasoned about and modified-- not a collection of output. It's not a point on a scatter plot, it's a waypoint towards a useful end.

Re: LLMs are not suitable for brainstorming

#67

Post by richardw »

vundercind wrote: post #20
jasonjmcghee wrote: post #10

Earlier quoted context omitted.

I agree with this, but also get so irritated with the endless praise. Like, tell me I'm wrong and tell me why. If I present a bad idea, tell me that. Or even like "huh? explain" Looking forward to ramping up the honesty parameter. Hoping OpenAI's new voice model trivializes this so I don't need to prompt engineer.

Me: “I’d like to start a business harvesting cat shit to fight global warming. People would pay me to take their cat shit and bury it because maybe it has carbon in it or something IDK I’m not a scientist. I would give them carbon credits in the form of a cat-shit-sequestration crypto token my business created. I’d pick up the cat shit by bicycle to save carbon emissions. Please help me develop a business plan.” Char…

I imagine the first models that trained on HN comments resulted in staff members resigning and becoming hermit alcoholics after some brainstorming and "Show HN" test runs. To make something that didn't result in instant and persistent despair likely meant a lot of sentiment analysis on input data, and the result is a system that is extremely pleased every time we show up.

Re: LLMs are not suitable for brainstorming

#68

Post by bcstyle »

Author here. Was not expecting this quick post being picked up by HN - thanks for all the comments!

I want to acknowledge that the original title is inaccurate, as many of you have pointed out. It should be "(current) LLMs don't brainstorm novel things really well" rather than just brainstorming.

It's not intended to be a clickbait though - I was kind of mixing two definitions of brainstorming unintentionally. When we refer to the group activity that aims to collect all angles from participants (and common wisdoms), LLMs are really good, and it's something I do on a regular basis. However when it comes to the hope of reaching novel ideas that don't exist before (which some of us will consider what distinguishes brainstorming from group discussion or research study), I would say today's LLMs don't do well. I've seen such issue in business and arts domains, and also someone here mentioned similar experience in video game design.

I would argue that (so far) for any idea LLMs tell us, there exists at least one instance of a similar pattern in the training data (either exact or in a high level). If this is what you need, then great. But some problems require more than that. And I would argue that a lot of important innovations in history didn't follow this pattern. I'm aware of reports on LLMs helping research (e.g. the works shared by Terry Tao), but I don't think they contradict the point here. Will be super happy to be proven wrong though!

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