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I find LLMs to be useful tools for brainstorming. I have often inadvertently found myself brainstorming just by explaining something challenging I am working on to a colleague with no expertise in my area. Just explaining forces new perspectives and new ideas. Similarly, LLMs are captive audiences for throwing out ideas and playing with them. The interaction creates something more than just talking to myself or a whi…
> 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…
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 always perfect, but even the ideas that don't really work can reveal something about the concepts involved. And bullshit often takes creativity to create, but that doesn't make it useful as actual creative output. It's not like the second you move beyond empirically provable statements, everything has equal merit. If you're trying to creatively work to a useful end, whether or not the knowledge you're working with is fabricated is pretty consequential. Doing otherwise would be like trying to optimize your code based on utterly fake but plausible algorithms-- sounding right isn't right enough to be useful. IMO, being able to create lies that pass the smell test is LLMs' most dangerous proclivity, especially when they're presented as expertise-in-a-box.
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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…
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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)
I find LLMs to be useful tools for brainstorming. I have often inadvertently found myself brainstorming just by explaining something challenging I am working on to a colleague with no expertise in my area. Just explaining forces new perspectives and new ideas. Similarly, LLMs are captive audiences for throwing out ideas and playing with them. The interaction creates something more than just talking to myself or a whi…
"LLMs are no good for [use case X]" often means "I aren't very good at using LLMs for [use case X]".
With many powerful tools - violins, say, or carpentry tools - we know that it takes a long time and a lot of learning to achieve competent performance, much less virtuoso performance. Someone who spent ten hours learning the violin and concluded "Violins sound terrible" wouldn't have diagnosed a problem with violins, but with their own mastery. I certainly think current LLMs have some big intrinsic weaknesses, but also that what they are is quite subtle.
Idk. In the vast majority of topics that intellectually stimulate me, I'm far below the average specialist. That means LLMs have a lot to offer me.
I'll also add that there's a big difference between "give me 10 startup ideas" and having a conversation with it to explore different startup ideas (for example). Through conversation you can build off what each other say and explore the space.
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
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 just couldn't get it to really think outside the box.
> 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 how do you know?