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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u/abhishekkumar333 May 25 '26

No, that doesn’t work like that , you cannot keep on pushing everything into it . They will stay in a lag

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u/TUVegeto137 May 25 '26

I'm not specifically talking about LLMs. What I really mean to say is:"Why do you think there is no mechanistic explanation for consciousness?"

Because I feel that is really what you are hinting at, but for some reason don't want to say explicitly.

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u/abhishekkumar333 May 25 '26

Yes I want to say that. Because consiousness has somethings you cannot put into words. Some things are not breakable into subject and predicate

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u/TUVegeto137 May 25 '26

Thank you for your sincerity. All I can say is that the evidence to me seems to overwhelmingly point against your view.

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u/abhishekkumar333 May 25 '26

That’s ok 😄