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this post was submitted on 31 Jul 2026
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I think the pace of development is such that it's only a few years before humans are no longer in the chain of decision making. It was just 2017 when the infamous transformer paper came out.
A stupid person would believe this.
"AI" in its current iteration is a distillation of human knowledge. It lowers the barrier to access to long standing programming libraries that make people think it is some sort of smart. It seems intelligent because it's imitating the things we have already created.
Yeah, that's what bothers me so much. It doesn't get "smarter" or imagine novel solutions. It simply has access to everything that's already existed.
I'm scared we're ~~gonna have~~ already experiencing some kind of intellectual slump because handing everything to the machine built on existing knowledge...doesn't yield any new ideas.
I'm sure they're still banking on human brains having new ideas, so they can simply steal them and feed those new ideas to the machine. Then they'll tell the ideator their brain is irrelevant thanks to the industrialized intellect-theft device.
The intellectual divide will be deepened significantly by "AI".
Ive never heard dumber conversations than people thinking "AI" is solving some hard problem. Here are a few examples:
All of these could easily be done before, people were just too stupid to know how to do it without typing a stupid prompt and wasting resources to do it.
I wonder if this whole phenomenon could be explained by a Dunning-Kruger type effect. Where dumb people see "AI" as a great solution, and those on the smarter side see straight through it as a loud over juiced parrot.
No need to wonder. You are spot on.
LLMs are incapable of reasoning. They just guess the next token.
Neurons are incapable of reasoning they're just firing based on a deterministic action potential. What are neural networks doing but creating internal models of reality and guessing what's next based on patterns?
LLMs do not fit as neurons in your comparison.
Brains can reason, LLMs cannot.
I'm not saying they are identical but they are similar in the sense that a neuron cannot reason. It's only in a quite large and densly connected neural network we believe there is reasoning.
But the closest equivalent of a neuron in the AI world would be a node, and I haven't been talking about that. So your comparison does not fit or make sense.
LLMs as a genre of AI research are incapable of reasoning. At best they can pretend to reason, and even then they are terrible at it.
I think both can more aptly be represented as a special type of graph like from graph theory. Once again fundamentally the human brain isn't reasoning on the level of neurons and most definitely atoms aren't reasoning
Once again that's a strawman.
We would've bullied those nerds more for misusing the word neuron. It was cute at the time, but now they're running around being all weird thinking that since they can pretend to read that one paper a better way to do one computer thing, it makes them experts in how brain works, just because there are similar words.
I don't think anyone who is aware enough is under the assumption that neural nets are a one to one replication of neurons. It's more of a special type of graph. That said one could also represent a human brain as a special type of graph.
The amount of good computer people specialised in ml, who think this knowledge gives them understanding of human mind that even neurobioligists don't posess is staggering. And depressing.
Also not really the point I was arguing. It's pretty clear NN are very different than a human brain. It does though give us some insight to minds more generally but I don't think current networks are on the order of complexity necessary to really be generating abstractions similar to a human neural network. That said there's strong arguments to be made about glimpses here and there like models spontaneously creating their own internal workspace like an inner monologue or quasi subconscious. To be clear I'm not saying it is aware or identical to a human mind but it's interesting to see it self assemlble similar looking structures without any direct guidance.
And that's the whole thing, I'm pretty sure it doesn't. The same way knowing how computer RAM works doesn't give you insight into how human memory works, even if the word memory is used in both cases. A bunch of llm bros think it does though.
The fuck they aren't. The token predictor predicts a token. The probability of a token is reinforced by human reactions to it. When it started generating words that usually describe inner monologue, humans started freaking out, which reinforced this probability. It's literally "say I'm alive - I'm alive" meme.
It gives us a good glimpse into human psyche however. It shows how easy it is to full people by pretend language, how willing we are to ascribe agency to anything that can pretend to write words. And even that's not new, ELIZA was 60 years ago.
What is the transformer paper
Worst people you know pretend they read a math paper from 10 years ago, and it gives them deep understanding of all the complex problems you can imagine. It's hard to overstate how much this one paper fried their brains. It's even harder to overstate how it's actually just one paper about computer math
The white paper on the fundamentals of the current AI push. Everything is for the most part based on that architecture from 2017 but with cleaver twist or two.
Just googled it: https://en.wikipedia.org/wiki/Attention_Is_All_You_Need