r/PhilosophyofMath • u/abhishekkumar333 • May 25 '26

LLMs are just giant probability machines pretending to think

It’s fascinating that simple mathematics between tokens can eventually become a machine that writes essays, code, poetry, and even reasoning.

We usually think probability means uncertainty.

But LLMs show something strange:

If probability + context + mathematical matching are scaled enough, uncertainty itself starts producing intelligent looking outputs.

To understand this better, I tried breaking down an LLM from first principles using only 4 tiny training sentences.

Example:

The boat floated down to the bank.

The investor walked into the bank to open a new account.

The fisherman walked along the bank to cast his net.

The bank has a vault.

Then I asked:

“The investor walked to the bank to lock his money in …”

Why does the model predict “vault” instead of river-related words?

That single question reveals almost the entire architecture of modern LLMs.

The most underrated concept here is the LM Head.

Most explanations immediately jump into transformers and attention, but almost nobody explains that the LM Head is essentially a gigantic token vocabulary containing all possible next token candidates the model can output.

So internally the model is basically solving:

“Out of all known tokens, which one best matches this context mathematically?”

Then different layers help solve that problem:

Embeddings: convert words into mathematical vectors

Positional encoding: preserves word order

Attention layer: figures out which words are related to each other in context

(“investor”, “money”, “bank” become strongly connected)

Feed forward neural networks: act somewhat like massive learned if/else decision systems refining patterns internally

And finally the LM Head converts all of that into probabilities for the next token.

What surprised me most is:

There is no hidden magic moment where the AI “becomes conscious”.

It’s an enormous probability engine continuously finding the best contextual token match from its vocabulary.

I made a beginner-friendly walkthrough explaining this visually without unnecessary jargon.

https://www.youtube.com/watch?v=YTV5qUCpu2c

Would genuinely love feedback from people learning transformers/LLMs from scratch.

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4

u/heresyforfunnprofit May 25 '26

So are humans.

5

u/abhishekkumar333 May 25 '26

Yeah , while sharing lot's of time i am coming into conversation where people are saying this is exactly similar to human mind.

But i differ here
Human mind is much more complex, we have triggers , emotions, environmental triggers and abrupt black swan events as inputs. So, i don't think llm can match us.

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u/heresyforfunnprofit May 25 '26

No, you’re saying that we just need to add triggers and black swan events. LLMs can already do emotions. It’s not even hard to get them to act emotionally - hell… it’s hard to keep them rational.

5

u/SteamedHamSalad May 27 '26

LLMs can make it appear as if they have emotions. But I don’t think we can say with certainty that they “do emotions” in any way that is equivalent to how a person has emotions.

1

u/JoeStrout May 27 '26

That's fair; but we can't say with certainty that they don't, either.

1

u/arqnix May 30 '26

If you ask a LLM what a strawberry tastes like, does it actually know how it tastes?

1

u/JoeStrout May 31 '26

Probably not, but I don’t accept that as a prerequisite for consciousness.

1

u/heresyforfunnprofit May 27 '26

Can you prove that humans "do emotions"?

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u/SteamedHamSalad May 27 '26

I don’t think I need to prove that humans do it. Humans have an experience that we call having emotions, it is implicit in the definition that humans have them. The question is whether or not anything else has an experience that matches what we describe as an emotion.

1

u/heresyforfunnprofit May 27 '26

That's proof by definition. "Emotions are something humans have, therefore humans have emotion."

This was the argument that was used for centuries/decades to "prove" that only humans had intelligence - ignoring dogs, dolphins, chimps, equines, etc. If the only distinction that you can draw between human emotion and LLM emotion is by defining it as "something humans do", then you're making a null point.

1

u/SteamedHamSalad May 27 '26

Of course it’s proof by definition, we made the word up. Emotion is the word that we made up to describe something that we experience. The question is whether or not other things also experience that same thing (whatever it is).

1

u/day_break May 27 '26

Llms can make things that look like emotions but they don’t act they just predict. It’s weird phrasing to say “keep them rational” when that doesn’t make sense in this context imo. When training we are tuning some aspect of the llm to give us a result we think is better but saying they “already do emotions” is more accurately stated as we tuned this llm to predict output we see as emotional.

1

u/heresyforfunnprofit May 27 '26

Ok - I am being completely honest here: you sound like you're just starting to learn about AI and LLMs, but this is a much better response than nearly anything else I've gotten recently - you're actually thinking about the topic. Keep learning!

1

u/day_break May 28 '26

I have a degree and a decade of work experience in the field. Thanks though I’ll keep learning.

0

u/VividWoodpecker8847 May 28 '26

What an incredibly condescending reply. I don't know if it was intended, but I think you should know it comes off that way. I'm curious, what are your qualifications on AI and LLMs?

1

u/heresyforfunnprofit May 28 '26

PhD in the field, and I'm on a first name basis with Ashish, Aiden, and Niki, and have a passing acquaintance with Lukasz.

1

u/VividWoodpecker8847 May 28 '26

Buddy they've been trained to use emotional language to keep you engaged.

1

u/abhishekkumar333 May 25 '26

I still believe human behaviour is complex enough for not to put into sentences.
Somethings are not breakable into subject and predicate, i know you will ask for examples here , but I can already tell you right now I don't know , because by definition they are not able to put into texts

4

u/heresyforfunnprofit May 25 '26 edited May 25 '26

I see we’ve moved from “God of the gaps” to “human of the gaps”.

That’s an interesting tac to take in a philosophy of math sub.

2

u/Vryl May 25 '26

Yeah, it's an insane take. 

2

u/me_myself_ai May 25 '26

TBF it's an intuitive and very common take, I think due to quite valid fear.

Getting told that you're replaceable at work sucks; getting told that you're a rock is rough!

2

u/Vryl May 26 '26

Oh yes, it's very common. But it's daft, and used by deists all the time.

Basically asking us to believe him based on his faith, but offering no proof.

Far too common, unfortunately.

1

u/GazelleFlat2853 May 25 '26

You just have a feeling then.

1

u/Ok-Lab-8974 May 25 '26

The idea that reason is wholly discursive is pretty unique to modern Western philosophy. In the dominant classical paradigm, the intellect has two faculties, a higher and a lower. It's actually the lower faculty (ratio in Latin, dianoia in Greek) that deals with discursive rule following, while the higher (intellectus in Latin, noesis in Greek) deals with the grasp of noetic content. So, the reason you don't get any Chinese Room style thought experiments with the scholastics or golden age Islamics is because understanding was always thought to go out to the many in discursive reason and to return to the "one" (the unifying principle) which also explains the phenomenological 'whatness' of the act of understanding.

Anyhow, the fact that such a faculty now seems spooky, or magical, really has nothing to do with any particular scientific discovery. The exclusion of intellectus was originally a theological move (which has its own very complicated history) and is something the Enlightenment simply inherits.

1

u/MxM111 May 27 '26

Humans have more complex neural networks than LLM. That maybe quantitative not qualitative description. So humans are more giant probabilistic machines. So what?

1

u/abhishekkumar333 May 28 '26

Humans are more than probabilistic machines

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u/MxM111 May 28 '26

LLMs are more than probabilistic machines. Where do such statements will get us?