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True for a lot of current AI. With more robotic bodies, loads more access to cameras/audio/satellite/science measurements, an AI can have original experience on a level that can only be described as god-like compared to humans.

I do think so. The difference is that, even apart from synthesis, the creative human knows how to filter out the shit ideas from the clever, subtle ones—LLMs seem to just run with the first…um, thought that… um, comes out of their head.

I suspect knowing that you've on to something special probably does require "human experience", woe, melancholy, "the human condition", reflecting on the brevity of life…

Yes!

Aside from the more fundamental questions about the nature of cognition and what constitutes intelligence, there's a practical matter: humans have life to learn from. We have a lifetime of persistent memories, an identity, a social life, physical interactions with the world of many qualitatively different kinds, and we're taken on a lifelong journey into different studies, workplaces, and living environments by the biological need to survive.

Even if human creativity is in some sense also recombinative at its core, we have a very different set of inputs from LLMs. Even under the (almost certainly false) assumption that human condition is basically similar in structure to an LLM, we should expect some differences in outputs based on these profound differences in inputs.

I still doubt that we have the knowledge to describe all of our human desires as mere results of our brain interacting with the nervous system either. There are many processes going on besides analysis and synthesis. If I plan on doing something extraordinary, I don't only sit there, think, and try to rearrange some pieces from memory. I'll go look around, touch, taste, re-explore and expand the perception my environment has to offer. Further, my perception can vary by the minute and I could even try to bring in a touch of chance whenever I feel like.

Wittgenstein's "whereof one cannot speak, thereof one must be silent" might be fitting here, yet language still continues to evolve.

No, they aren't. I'm not sure why it's such a popular narrative that all art is just some kind of recombination of existing things; it's not. Actual lived experiences are unique and impact what is created. Novels written by people in post-Revolutionary France are not the same as novels written by post-WW1 France. Events in history shape culture and introduce new ideas and experiences that weren't there before.

The gap is that the data humans have access to is much more analogue, emotional, and grounded in the real world compared to the data that AI is currently trained on.

That's the problem with your argument, right here. Emotions are not merely portable "data," and framing this way is a problem from the start.

I don't think you get human experiences without actually being human. The most perfect LLM copy of a mind is just the copy of externalized output.

I agree, yet I also think AI is extremely limited in terms of new creativity.

My guess is that humans operate on some deeper level. Much like the grokking model example where it easily trained on the training data, but only later did it really start to understand the deeper problem space and 'grok' the problem, I think LLMs are doing something similar with human thought. LLMs can throw more compute, but they are still lacking some introspection/drive that leads to the better creativity of humans. Grokking this from the training data might not be possible, or it might take some fundamentally different approach, or even an imperfection in humans that LLMs don't have (ego/drive?).

This isn't to say that LLMs could never do it, but the cost to do so might require magnitudes more scale in training times and size. Or it could be in the next model released. Or maybe they already can, but that gets trained out in favor of overall more general correctness accross all domains.

Do I reflect on the objectively correct structure of the story? Do I "agree" with everything Dostoevsky is saying? Not really.

I don't know if this offends literature people or not. But this sure as hell is incompatible with the AI bro paradigm in which all thought can be objectively reduced to some shared standard to benchmark on.

My position will be read into as deep irrationality from many opposing positions, but it's fine.

Now, none of this doesn't "preclude* the ability for AI to have the same kinds of network effects. Of course it can - that's what I've been saying for the longest time. But don't confuse, becoming integrated with society, with this ideal of superhuman X.

Now of course, you could argue, "there is no such thing as anything else besides becoming integrated with society. There is no other standard that works." Very good! Darwinian-adjacnet positions are interesting. This is a position - but then don't claim it's equivalent, or god forbid, the exact same, as the "super AGI" ontology. These require fundamentally different assumptions about what justified what, and an attempt to try and pretend otherwise is sophistry.

Superhero Wars Trek 42 - the latest franchise installment, billion dollar Hollywood budget, financed and produced by billionaires, audience tested committee-made script, lots of people involved, designed primarily to push merchandise.

Personal Story - a movie about someone's personal reality or fantasy, something typically not made by studios because the story isn't profitable to a wide audience, painstakingly generated and edited by one person using AI, designed primarily to tell a story.

I put up a different strawman because your strawman is too beatable. As humans, of course we're all interested in what other humans have to say. But you haven't explained why you feel people can't use AI to say things, or why AI output can't be based on a real human's life experiences.

Personally, it seems like movie studios are the ones with only 7 stories to tell, and I've seen the movie and its sequel, the prequel, the requel, the remake, the gritty reboot, the musical, and the animated series. I'm excited that AI will let people skip the studio gatekeepers to tell some new stories for a change.

I think there's a lot to learn on how we really process information.

For example, a child learns that "foreigner" means someone from outside their country. Then, when they're 11, they go on their first holiday abroad and realise "Wait! _I_ am a foreigner here!"

So, maybe one way to frame what you're saying, is that LLM output tends towards being easily assimilable.

It's... almost an oxymoron, and very different from my experience.

Your subjective experience matters in this case. Almost completely.

Here’s what I did: 1. Install Jomo on the phone. There are other apps, but basically it makes me wait 5s before I can open a brainrot app, and then I can only use it for 5min, and every time I do this I have to wait an additional 5s. It resets at midnight. This introduces the necessary friction.

2. Paper books. The house is now full of paper books. Book seems interesting? Buy it. Books everywhere. Real books.

3. The actual habit. I stack habits. Right now I have a daily workout routine. First thing I leave the house and either run or go to the gym. I bring my book, and afterwards go to the cafe across the street for a coffee. At night, I read before going to bed. Once you finish a few books this way, you’re in. TV now is actually hard to pay attention to, and I feel kind of… dirty doomscrolling now (like eating junk food, it tastes good but you feel gross during the experience).

If you want something to start with: https://bookshop.org/p/books/true-grit-charles-portis/5ac454...

- "The Spanish Civil War" by Paul Preston

- "Homage to Catalonia" by George Orwell

Books on the same topic on my reading list (and quite frankly can't wait to get hold of them):

- "The Spanish Civil War" by Hugh Thomas

- "The Fight for Spain" by Antony Beevor

Though this might be me as a British reader, simply preferring a rather less American turn of phrase.

I reckon the more transatlantic, english-as-international language DeepMind team have had a subliminal (or maybe deliberate) impact on the way it chooses to write.

Or perhaps small open weights models simply aren't under the same commercial pressure to be engaging and sycophantic and are therefore less likely to adopt the samey overly casual, upbeat, Californian sales assistant manner. (Don't get me wrong, I like this from real human Californians just fine!)

Either way, the default tone is much less showy. I would be interested to find out if you agree.

I am very much an LLM cynic. I am engaging because I must, and trying to learn fundamentals, but I would not say I am overly excited by any of this, just glad that small open weights models exist as a counterpoint.

I loathe the way ChatGPT writes, and the Claude-isms that are everywhere; it is actually quite enraging, especially when you start seeing it in internet comments from people who used to try to write out their own thoughts.

But in my experiments with open weights models I have found I am much less aggravated by summaries and outlines written by Gemma 4, so much that I am happy enough to read them, because they have fewer irritants that take me out of the reading flow.

Though this evening it told me very kindly that my photography is a bit "safe". How very dare it… understand me that well.

This seems to be a hard problem for LLMs, as passing would probably require good self-perception ("oh no, I am writing like an AI!") and fine-grained control over its own output ("let's write like a human instead!").

Of course, the amount of self published work has also helped make the lack of a good copy editor noticeable. I can excuse self published blogs though. But the stuff released "professionally" has really become farcical.

I have a stupid AI app I use now for some bookkeeping which was previously, just an excel sheet. except it has a UI, it validates inputs, and does a bunch of other housekeeping stuff that makes it nice. Did the excel work? yes totally.

This is incredible!

Why don't you just use whatever LLM you have on hand to summarize every book you could read instead of reading it? The idea that ai slop is 'better' because you can distill the idea is an insane point to me because it treats books as a pure consumption-based concept, where the goal is strictly to finish a book and move on.

I think even the worst book is more valuable than whatever garbage an LLM writes because you can at least learn from the intent. Where and why the author failed, where they got stuck, the points they failed to make. LLM writing is a void, there's nothing to be learned.

Nobody did any original research, you didn't discover gravity, and you didn't participate in any historically significant events.

Yet we say that people who have been through education know about such things.

However, general purpose LLMs like Fable have been trained on huge amounts of all kinds of data, and therefore find it exceedingly hard to break out of the grooves carved by that data. They can’t avoid defaulting to centroids and averages, even when they are trying not to. This makes it possible for classifiers like Pangram to discriminate their writing.

A plausible way to work around this limitation would be to train a LLM on a limited and cohesive subset of writing materials, so it would absorb their specific writing style.

One example might be Talkie, a LLM trained on pre-1930’s English text. Talkie is a far smaller and less powerful model than Fable.

And yet, Talkie’s writing is so distinctive that it is often classified as human by Pangram.