[famouswaffles]

>I know my world model is fundamentally incomplete. Even more foundationally, I know that there is a world, and when my world model and the world disagree, the world wins.

Yeah this isn't really true. There's not how humans work. For a variety of reasons, Plenty stick with their incorrect model despite the world indicating otherwise. In fact, this seems to be normal enough human behaviour. Everyone does it, for something or the other. You are no exception.

And yes LLMs can in fact tell truth from fiction.

GPT-4 logits calibration pre RLHF - https://imgur.com/a/3gYel9r

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback - https://arxiv.org/abs/2305.14975

Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334

Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221

The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets - https://arxiv.org/abs/2310.06824

Your argument seems to boil down to "they can't perform experiments" but that isn't true either.

[user_named]

It is a very basic fact that LLMs have no concept of true or false, it only has an ability to look up what text data it has seen before. If you do not understand this you are in no position to discuss LLMs.

[SpicyLemonZest]

I really don't know what people mean when they say this. We routinely instruct computer chips to evaluate whether some condition is true and take action on that basis, even though the chip is "just" a selectively doped rock. Why would the details of an LLM's underlying architecture mean that it can't have a concept of true or false?

[xcv123]

One of the most ridiculous comments I have read about LLMs here.

The ~100 layer deep neural networks infer many levels of features over the text, including the concept of true and false. That is trivial for an LLM.

Are you completely unaware these are based on deep neural networks?

Convolutional Neural Networks don't operate by "look up" of text data.

[user_named]

Okay, so then tell me how does it decide whether it is true or false that Biden is the POTUS?

It's response is not based on facts about the world as it exists, but on the text data it has been trained on. As such, it is not able to determine true or false even if the response in the above example would be correct.

[jeffparsons]

Serious question, in pursuit of understanding where you're coming from: in what way do you think that your own reckoning is fundamentally different to or more "real" than what you're describing above?

I know I don't experience the world as it is, but rather through a whole bunch of different signals I get that give me some hints about what the real world might be. For example, text.

[Guvante]

You understand the concept of true vs false.

LLM does not, that isn't how it works.

You can say the difference is academic but there is a difference.

What is the difference between a real good faker of intelligence and actual intelligence is an open question.

But I will say most AI experts agree that LLM are not artificial general intelligence. It isn't just a lack of training data, they just are not of the category that we mean by that.

[xcv123]

> You understand the concept of true vs false.

> LLM does not, that isn't how it works.

GPT-4 can explain the concept when prompted and can evaluate logic problems better than most human beings can. I would say it has a deeper understanding of "true vs false" than most humans.

I think what you are trying to say is that LLMs are not conscious. Consciousness has no precise universally agreed formal definition, but we all know that LLMs are not conscious.

[edflsafoiewq]

In order to affirm something is true, you don't just need to know it, you need to know that you know it. LLMs fundamentally have no self-knowledge.

[xcv123]

> LLMs fundamentally have no self-knowledge

ChatGPT can tell me about itself when prompted. It tells me that it is an LLM. It can tell me about capabilities and limitations. It can describe the algorithms that generate itself. It has deep self knowledge, but is not conscious.

[user_named]

LLMs only knows it's text embeddings. It does not know the real world. Clear?

[xcv123]

Humans and other creatures only know their sensory data input. Therefore they also don't know the real world.

Your eyes and ears perceive a tiny minuscule fraction of what is out there in the real world.

A blind and deaf person must know even less of the real world than an LLM, which can read more than a human can ever read in their lifetime.

[ChatGTP]

It’s giving the most likely answer as opposed to the factual answer?

[xcv123]

> It's response is not based on facts about the world as it exists, but on the text data it has been trained on

How did you find out that Biden was elected if not through language by reading or listening to news? Do you have extra sensory perception? Psychic powers? Do you magically perceive "facts" without any sensory input or communication? Ridiculous.

By the same argument your knowledge is also not based on "facts" about the world, since you only learned about it by reading or listening. Absurd nonsense.

[user_named]

You didn't answer my question ergo you concede that LLMs don't know true or false.

[xcv123]

I did answer your question indirectly. By the reasoning in your argument, you yourself also don't know true or false. Your argument is logically flawed.

Do LLMs know true or false? It depends on how you define "know". By some definitions, they "know true or false" better than humans, as they can explain the concept and solve logic problems better than most humans can. However, by any definition that requires consciousness, they do not know because they are not conscious.

The average person spends a lot of time completely immersed in "false" entertainment. Actors are all liars, pretending to be someone they are not, doing things that didn't really happen, and yet many people are convinced it is all "true" for at least a few minutes.

People also believe crazy things like Flat Earth theory or that the Apollo moon landings were faked.

So LLMs have a conceptual understanding of true/false, strong logical problem solving to evaluate truth or falsity of logical statements, and factual understanding of what is true and false, better than many humans do. But they are not conscious therefore they are not conscious of what is true or false.

[robbrown451]

It certainly doesn't "look up" text data it has seen before. That shows a fundamental misunderstanding of how this stuff works. That's exactly why I use the example above of Alpha Zero and how it learns to play Go, since that demonstrates very clearly that it's not just looking things up.

And I have no idea what you mean by saying that it has no concept of true or false. Even the simplest computer programs have a concept of true or false, that's kind of the simplest data type, a boolean. Large language models have a much more sophisticated concept of true and false that has a lot more nuance. That's really a pretty ridiculous thing to say.

[user_named]

Yes, you don't understand what I said. The model has no concept of true or false. It only has embeddings. If 'asked' a question it can see if that is consistent with its embeddings and probabilities or not. This is not a representation of the real world, of facts, but simply a product of its training.

[robbrown451]

"This is not a representation of the real world, of facts, but simply a product of its training."

Tell me how that doesn't apply to the human brain as well.

[jeffparsons]

They have no inherent concept of true or false, sure. But what are you comparing them to? It would be bold to propose that humans have some inherent concept of true or false in a way that LLMs do not; for both humans and LLMs it seems to be emergent.