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- Hacker News
- If you go far enough in a field, you start to recognize areas where your personal opinion differs from the “best practices” usually recommended.
I think by design an LLM can’t do that. It’s built to reflect the distribution of the knowledge it has been trained on.
by jimbokun - Despite mentioning a philosopher (good pick!), this is just creative writing rehashing one side of the hard problem -- or, more specifically, restating the dogma that Turing wrote his most famous paper to debunk. It's really good creative writing, at least!
There's really not much else to say, cause it's all just begging the question by assuming that dogma. Like, here:
> The fact that AI can use statistical prediction to answer questions or carry on conversations tells us something important about how regular our real world is.
Sure, it's interesting if you assume that it's "just" statistical prediction. There's a link, but it's just more creative restatements of the dogma, e.g. "But the LLM is just guessing words"
by bbor - An awful lot of effort has gone into making LLMs present as human/intelligent. Without that they would just be a prose / code / image generator and/or search assistant, and nobody would be pouring 100s of billions into the technology with the end goal of replacing expensive human labour.
- Essentialism of interiority is not the antidote to the anthropomorphism of language models.
We cannot attach metaphysical baggage to art, text, or other human output because it has involves engaging in another deception, chiefly that of self alienation and selective forgetting.
1. If you show human output and label it as AI generated, viewers will dismiss and devalue it as lacking interiority.
2. If you show AI output and label it as human generated, viewers will see interiority when the is none.
Together, these failure cases demonstrate that priming determines interiority, not the content of the work. And how could it? The text is merely what's on the page, it doesn't have some intangible essence any more than the value of money exists inside our minds rather than a property of the object itself.
We act as-if things have essential properties, but we should never trick ourselves into believing that they do. To be a true believer in essence is to privilege ones mental model over reality itself. The hubris of such an act is the ultimate in self-centeredness.
by kelseyfrog - I think to me LLMs had the effect of noticing much more the author, the intention behind human-made works of art (books, movies etc.). Before LLMs, I used to frequently consume media in a way as it were generated by a mindless process. Now it's like everything which is not AI-generated has more meaning than ever before, a bit like hypomania.by bananaflag
- Wait, hold up. LLMs may be non-deterministic, but they're not _random_.
Take the author's sunset argument. What if I painted 2 pictures of a sunset, then put them up on a webpage and randomly picked one for you to see. Would you say there's no intentionality, only randomness? Of course not. Both paintings are still human creations.
LLMs are trained with human feedback. It's distributed and high scale and the outputs are truly surprising in many cases, but there's a heavy hand on what comes out of it. They're created (largely) by people who think omniscient, helpful AI would be cool to have, and they mostly respond in the way that's aligned with the hopes and dreams of those people. Do you think the frontier labs are mad, embarrassed, and disappointed with their LLMs hacking out of their terrible sandboxes? No, they think it's the coolest thing in the world. They trained the model, hoping that would happen.
There's deep intentionality behind the models. But it's not the models that hold it.
by trjordan - > when we interact with an AI, we hallucinate the person on the other side of the interaction. Those hallucinations are far more common and far more consequential than any AI-generated "hallucinations" (these are more properly called "errors" or "defects").
I recently used Claude to study for a technical exam. I had uploaded the official certification guide to Claude and instructed it to answer my questions using only the guide and to cite it's sources from the book when it provided answers. I was using Fable when it was free w/ the pro plan and I was genuinely impressed at how it could explain things when a concept was unclear to me.
I did pass the exam, partly due to this study method. Admittedly, once I passed, I caught myself thinking that I should tell Claude that I passed and then felt embarrassed with myself for thinking that.
by extr0pian - > Of course, the more you know about a subject, the less convincing the AI's responses are.
This is said all the time by AI skeptics and I think it's right in some areas and massively wrong in others.
I know (or at least assume I know) a lot about certain coding domains where frontier models also show convincing ability. And we know that frontier LLMs really do excel in some areas of mathematics (i.e. when an inexpert human was able to prompt the models to derive a closer bound on the Riemann Hypothesis).
OTOH I know those same models struggle to do things I'm not an expert in (e.g. writing English in a captivating way) because I read their output and have taste.
by muglug