People still don't understand in 2026 that emergent properties can't be negated by the underlying mechanism. By that logic human thought is just electrochemical signals propagating through neural networks.

> it does not know

Define "knowledge" in a non-circular way.

There's a certain type of knowledge that machines definitely can't have - experiential - but conceptual knowledge doesn't inherently require subjective experience or a biological substrate.

> the only thing it does is reproduce patterns more or less abstract in function of the pressure you put on certain representation during training time.

As for humans; just replace "training" with "education" and the likelihood of a certain output with the likelihood of a certain thought or response.

Amusingly (in this context), much of adult behavior is shaped by patterns reinforced during childhood.

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edavison1 3 hours ago | parent | next [-]

While one can quibble with its argument, Gettier's conception of knowledge as justified true belief (prob familiar to many philosophy undergraduates) implies that machines can't in fact accrue knowledge. The idea that knowledge can't be defined in a non-circular way is only plausible for someone with no familiarity with epistemology.

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coldtea 3 hours ago | parent | next [-]

>Gettier's conception of knowledge as justified true belief (prob familiar to many philosophy undergraduates) implies that machines can't in fact accrue knowledge.

Nothing about the conception of knowledge as "justified true belief" implies that machines can't accrue knowledge.

For that to be the case "belief" would have to be defined in a circular way to exclude machines (which we can reject), or "justified" would have to be restricted to mean "based of observation of the external world".

The more general "based on observation of their input" applies to both men and LLMs.

That man can't know the bare direct facts of the world, just his own input (it's sensory experiences, and whatever second hand input he's given by other people), and for neither can he be sure they're absolutely true, or that he got right.

>The idea that knowledge can't be defined in a non-circular way is only plausible for someone with no familiarity with epistemology.

The idea that this or that epistemology restricts what can be the case in reality is only plausible for someone with no familiarity with epistemology.

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marcus_holmes 3 hours ago | parent [-]

> Nothing about the conception of knowledge as "justified true belief" implies that machines can't accrue knowledge.

They can't accrue knowledge because they stop learning once their training is finished.

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gchamonlive 2 hours ago | parent | next [-]

By this definition if they could instead buffer recent facts and then offload to their weights reliably and efficiently they would be able to accrue knowledge despite their substrate.

	▲	marcus_holmes an hour ago \| parent [-]
		Yes, and they'd have to deal with the same problem that we do: how do we know what is true? what gets counted as a "recent fact" and what gets dismissed as mere opinion or disinformation? In training they get feedback. Out of training, not so much. Hard problem

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coldtea 2 hours ago | parent | prev | next [-]

Humans stop learning once their training is finished too, it's called death.

The difference is that LLMs we can talk to them when they're in that dead state.

And of course for an LLM this is an implementation detail. One could just as well keep updating the weights of the same model over time. And its being done, it's called "continual learning". LoRA is also a way of doing that.

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Sharlin 2 hours ago | parent | prev [-]

You mean they don't accrue knowledge during the training?

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stygiansonic 2 hours ago | parent | prev | next [-]

Gettier actually criticized justified true belief (JTB) as insufficient for knowledge and provided counter examples known as Gettier problems

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pizza234 3 hours ago | parent | prev [-]

> Gettier's conception of knowledge as justified true belief (prob familiar to many philosophy undergraduates) implies that machines can't in fact accrue knowledge.

Ha. Gettier actually argued that justified true belief is insufficient for knowledge, not that machines can't possess it. And JTB doesn't inherently exclude machines.

Interestingly, research suggests LLMs encode truthfulness in their internal representations: https://aclanthology.org/2023.findings-emnlp.68/

	▲	stygiansonic 2 hours ago \| parent [-]
		Indeed. In fact this criticism of JTB is known as the Gettier problem: https://iep.utm.edu/gettier/

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627467 23 minutes ago | parent | prev | next [-]

> By that logic human thought is just electrochemical signals propagating through neural networks.

This argument keeps getting rehashed. The point is not the signal. The point is where/how the signal travels which in the human is affect by much more than whatever concept that can be represented by words.

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King-Aaron 3 hours ago | parent | prev | next [-]

As much as I flatly do not believe LLMs can have anything close to consciousness, I definitely agree that the argument of them being just a probabilistic word matching engine can also be applied to our own brains lol.

	▲	hsuduebc2 2 hours ago \| parent [-]
		Agreed. It's quite hilarious that its basically biological probabilistic machine flexing on silicon probabilistic machine. On top of that that silicone one is right here.

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mrheosuper an hour ago | parent | prev | next [-]

Imagine one day in the far future 21xx, we decide that machine actually has conscious since the 202x, and people in the future look back at us in horror: The kill(create new session) an "Android" without second thought, whenever they want.

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anon373839 3 hours ago | parent | prev | next [-]

I think the idea of emergent properties in LLMs is less and less relevant. Yes, the first few times they scaled pretraining and such models could do few-shot tasks was quite interesting. But the models we use now are really the product of extensive RL hillclimbing on a wide array of curated tasks. What’s interesting now is that the tasks they’ve been fitted to (long running tool call chains interleaved with reasoning tokens) do very useful things.

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santadays 2 hours ago | parent | prev | next [-]

I genuinely don’t know why people feel so certain about things like this. It’s like they mix up salience with reality.

I mean what can a person really be certain of, an experience is happening. I might be wrong about everything or confused. But I know I am having an experience. Do I know other people are? No. I assume they are.

Ask an llm what is truth that it is most certain is true. It will answer something similar. Do I believe it is conscious, no. But I also believe “I” exist, which is weird because where is the boundary between “I” and everything else.

So ok, we create meaning, not truth. Maybe just accept that.

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monk_grilla 2 hours ago | parent | prev | next [-]

> There's a certain type of knowledge that machines definitely can't have - experiential

Can you justify this? Do you mean currently or ever?

I can certainly imagine a future architecture where I would describe a machine as capable of accruing knowledge through its experiences (read: experiential knowledge).

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snypher 3 hours ago | parent | prev | next [-]

>human thought is just electrochemical signals propagating through neural networks.

Is it not? Or are we discussing existence of a soul etc.

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esjeon 2 hours ago | parent | prev [-]

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