alt Hacker NewsBut they generate objectively bad text. Why do you need an assistant to do that?
Perhaps for some uses (say a summary of some business document, or generating code which is then discarded or edited) that's acceptable. For literature, do you really feel they are useful tools? So many changes would be required IMO that you're better off just writing the story you want to tell.
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> But they generate objectively bad text.
They don't. I don't think people are taking full advantage of their capabilities. They produce perfectly functional prose. Sometimes, they produce something genuinely amazing to read. But that is quite rare.
People should stop expecting brilliant prose from LLMs without doing the preparatory work themselves first. Very few human authors can manage that in any case
> But they generate objectively bad text.
By default, yes. That's exactly the same for code: by default, even with planning and patient nudging towards best practices, you get passable code at best. Not elegant, not performant, and not particularly readable, either. Basically, an uninspired salaryman type of code.
In both domains, you can get much better results in some specific circumstances. Prompt, skills, memory, and the task must align, but when they do, you can get good quality building blocks that you can then work with. It's crucial to recognize the instances where there's a chance of getting better-than-average results and ones where you could dump your whole week of tokens into and still end up with a mess. This is a skill of the LLM operator.
Once get that skill, the only issue is capitalizing on it: basically, how you fit handling of the generated building blocks into your workflow. If it's seamless, it can be a big win. If it's not - yeah, writing by hand from scratch is often better.