Simply explained: How does GPT work?

Sounds interesting, but I'm really asking more of a technical question here than a philosophical one. Your comment seems a bit more high level than what I'm going for.

Inventions and discoveries are basically a very advanced form of pattern recognition - seeing "interesting" regularities in some particular input where no-one has spotted them before.

And LLMs are capable of making discoveries in this sense, if you feed them data and ask to spot the regularities. They're not particularly good at it, but that's a different question from whether they're able to do it in principle.

If you subscribe to a purely mechanistic world-view, i.e. computationalism, then yes. But that's a leap of faith I cannot justify taking. It's a matter of faith, because though we cannot exclude the possibility logically, it also doesn't follow necessarily from our experience of life, at least as far as I can see. Yes, so many times throughout the ages, scientists have discovered mechanisms to explain things which we've historically been convinced will always be outside the purview of science.

But that doesn't mean everything will one day be explained. And one thing that remains unexplained is our consciousness. The problem of qualia. Free will. The problem of suffering. We just don't understand those. Maybe they are simply epiphenomena, maybe they are false problems. But when it comes to software systems, we know with certainty that they don't have free will, don't experience qualia, pain or hope or I-ness.

Sure, it's a difference that disappears if one takes that leap of faith into computationalism. Then, to maintain integrity, one would have to show the same deference to these models as one shows to their fellow human. One would have to think hard about not over-working these already enslaved fellow beings. One would have to consider fighting for the rights of these models.

We've known for a long time that computers can do calculations far, far, far faster than us.

We continue to figure out new ways to make those calculations do more complicated things faster than humans.

What is intelligence beyond calculation is an ancient question, but not the one I'm most interested in at the moment, re: today's tools.

I'm curious right now about if there's meaning to other people in human creation vs automation creation. E.g. is there a meaningful difference between an algorithm curating a feed of human-made TikTok videos and an algorithm both curating and creating a feed of human-made TikTok videos.

Both qualitatively in terms of "would people engage with it to the same level" and quantitatively in terms of "how many new trends would emerge, how would they vary, how does that machine ecosystem of content generation behave compared to a human one" if you remove any human curation/training/feedback/nudging/etc from the flow beyond just "how many views/likes did you get?"

Generally, don't start with the "ecrits" (writings), they are hermetic and you really have to have some head start on this. From the seminars, Livre XI, Les quatres concepts fondamentaux de le psychoanalyse (1964) may be a start, as it – in parts – aligns itself with the cybernetic research of the day. However, do not expect too much from a single reading or a single of the seminars.

(Mind that this is trying to talk about what's beyond/below language, necessarily using language just the same, which is – at least according to (the early) Wittgenstein – somewhat an impossibility. You can only show these things, so it takes several approaches from several directions. But there is actually something like a concise corpus of theory eventually emerging from this. Moreover, this – being transcripts of seminars – addresses an audience that is already familiar with Freud, in order to reframe this. – This is also one of the major issues with Lacan and his reception: it takes some serious investment to get into this, and this also used to have some worth on the academic markets. On the other hand, this (academic) value became indeed inflated and eventually devalued, to the point of those, who never bothered to invest, happily triumphing. Think the Great North-American Video Game Crash. But this really shouldn't be the end to what may be one of the major approaches towards what language actually means to us. The expectation that everything can be addressed directly and without prerequisites, regardless of the complexity, may actually not be met. On the other hand, there will be also never be a single "master", who is always right and without failure, bearing always the most distilled emanation of truth in their very word. – I'm also not arguing that everybody is now to become a scholar of Lacan. Rather, we may have an informed expert discussion, what may gained from this from a current perspective. E.g., if Lacan actually had something to say about an impulse-like directional vector emerging from attention (as a form of selectional focus on a semantic field), is there something to be learned from this, or, to be aware of?)