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> LLMs seem already to be pretty good at translating

I often use LLMs to translate from "shitty English" to "good English". The substance remains the same but it's nicer to read.

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> Root cause here is that writing is how humans communicate ideas.

Writing is a way humans communicate ideas. It's not the only way humans communicate ideas. And now, it's not only humans who communicate ideas, we just saw with the OpenAI HuggingFace hack how AI agents were able to communicate amongst themselves by using various hacked websites to opportunistically write notes for later agents to use.

All that "X is a thing only humans do" type of circular definitions will buy you, is to expand the definition of what humanity is. And I doubt that's really what you think.

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I think you're missing the context, which isn't musing on what it is to be human and can machines think, but the purpose of Joe Smith's LinkedIn account expressing that he has ideas about X is to convey the message that Joe Smith is interested enough in X to venture an opinion on it, and Joe Smith has actually just set up an automated process to generate content without thinking about X, that perverts the purpose of communicating that Joe Smith is interested enough in X to propose the following ideas he been thinking about...

Similarly if Joe's contribution to his long form "idea" is a couple of bullet points, a program trained on flowery phrasing and a weighted average of everyone else's ideas isn't communicating Joe's thoughts on the topic, it's just adding words.

The debate on whether Claude actually thinks or not is orthogonal to the fact that outsourcing your "thought leadership" to it is avoiding thinking or leading. If I want to know how Wikipedia or Claude summarise wider human thought about the topic, I can find their websites thanks

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I get the context, but then the comment I'd replied to would have said that humans get better at communicating their ideas by writing their ideas on their own, rather than that writing is some kind of human-only mode of exposition. It's not.

And nor is an LLM generating text just "copy/pasting a Wikipedia article", you'd think people on HN would be smarter than that at least.

If all Joe Smith is going to do is cat $(which claude) to his LinkedIn, then he'll deserve the poor results he gets from it, but we shouldn't mistakenly say that this will be because LLMs simply cannot write. It would be just as dumb for Joe Smith to do with with a professional human ghostwriter.

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> An LLM written thing isn’t doing that, it’s something equivalent to copy/pasting a Wikipedia article.

Nonsense. I’m not sure whether this was ever an appropriate description of what LLMs do, but either way, they have obviously moved way, way beyond that.

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You are right, writing by AI is far less trustworthy or reliable than copy and pasting wikipedia.
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Absolutely agree. A modern agent is a sophisticated tool that can link multiple sources together to create a coherent piece of information hyper-specified for an audience. However, if humans have outlines that are expandable by LLMs it makes the most sense to do that as late as possible.

I don’t like reading AI writing either but I’m sure that’s a transitory period. Single prompt text expansions are unlikely to be useful because they’re late-bindable. You could give the original to me and I might be able to understand better.

But a series of steering prompts with various sources brought in is a different story. At that point it’s just a question of whether the agent can put together good information and their current inability to do so is unlikely to mean an inherent problem.

Some kind of UI affordance for this might help: with the agent emitting tags that allow for auto-folding or expansion in a way that allows both concise text and exposition when required by the reader. Mechanical sympathy, but for code executing on a human: good old human sympathy if you will

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