this post was submitted on 18 Oct 2023
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Current LLMs being bad at it doesn't mean they'll always be bad at it. Their current state is the worst they're ever going to be, and we're talking about a hypothetical future here. I don't see any reason why they can't be improved into a state usable for writing a story with all the worldbuilding details provided.
Your claim was about current LLMs.
But it's a fundamental limitation of what LLMs are. They are not AI. They do not have anything in common with intelligence, and they don't have a particularly compelling path forward.
They also, even if they weren't actually terrible for almost every purpose, are obscenely heavy and what we're calling "current" isn't something capable of being executed on consumer hardware, dedicated card or not.
Finally, the idea that they can't get worse is just as flawed. They're heavily poisoning the well of future training data, and ridiculous copyright nonsense has the very real possibility of killing training further even though training on copyrighted material doesn't in any way constitute copyright infringement.
Maybe open source LLMs aren't up to the task, but proprietary ones certainly are.
Also, you wouldn't really need a LLM, just a FM that you fine tune for your specific purpose.
What's this thing you call FM?
It's a foundation model. Basically it's the base algorithm that you train with data. LLMs are FMs that have been trained with an enormous amount of data, but they aren't necessary for every application, especially if you only need the AI/ML to perform a specific task.
Fine tuning an FM is just feeding it your own data.
No, they aren't. They aren't a little short of capable. You could multiply their capability overnight and have no shot of not immediately being the worst written game ever made.
There's a huge difference between stringing together words in the shape of a story and actually putting together something with a shrewd of cohesion. We're not talking mediocre here. We're talking laughably short of absolute dogshit.
Buddy, I have actual training in AI/ML from some of the leading engineers in the field, and my job leverages AI/ML very successfully to do a task really similar to what OP is looking for.
Maybe the versions available to the public to play with aren't up to the task, but using AWS Bedrock you can absolutely get results like OP wants.
You and the other 5 million companies hemorrhaging money on extremely heavy operations that are universally fucking terrible.
If you're willing to claim LLMs are even 1% of the way to what he asked for, you either have absolutely no clue what the tech is or you're a scammer trying to steal money from people.
The cutting edge of LLMs have nothing in common with intelligence.
Since you clearly can't read, I'm done discussing this with you. Maybe pick up a book and improve that reading comprehension a bit.
I can read perfectly fine.
You claiming to be an expert when your assertion proves that it's literally impossible for you to be is simply not persuasive. You're doing the equivalent of claiming to be a geologist while arguing for a flat earth. It's inherently proof that you're full of shit.
Right, I see where the confusion comes from. I mention current LLMs to say that the architecture and pre-training procedure we currently have produce models that are already capable of generating the type of outputs that can be used in this context. I make no claims about the quality of the output, but some additional fine-tuning on the game's specific story can take things very far.
When you say LLMs are not AI, I'm guessing what you mean is that they are not artificial general intelligence (AGI), and that I agree with. But AI is very broad, including things as simple as A* search. Decision trees aren't any more AGI than LLMs and they've been able to produce some very compelling stories, so this isn't a very good argument. We don't need AGI to write good stories.
The compute resources required for these models is something that can be fixed as well. On the hardware side, consumer hardware are continuously getting more powerful over time. On the software side, we're also seeing a lot of great results from the smaller 7b parameter models, and these are general purpose language models. If you just need something for your one game, you can likely distill the model into something much smaller.
The training data that we used for the current generation of LLMs are already out there and curated. We know that this dataset can achieve the performance of today's LLMs, and you can continue to train on that same data in the future. As long as you control where your new data comes from, this is not an issue.