5 ms·

The difference is that "the world" is not exhaustible in the same way as Go is. While it's surely true that the number of possible overall Go game states is ext

by lsy 3y ago

The difference is that "the world" is not exhaustible in the same way as Go is. While it's surely true that the number of possible overall Go game states is extremely large, the game itself is trivially representable as a set of legal moves and rules. The "world model" of the Go board is actually just already exhaustive and finite, and the computer's work in playing against itself is to generate more varied data within that model rather than to develop that model itself. We know that when Alpha Zero plays a game against itself it is valuable data because it is a legitimate game which most likely represents a new situation it hasn't seen before and thus expands its capacity. For an LLM, this is not even close to being the case. The sum of all human artifacts ever made (or yet to be made) doesn't exhaust the description of a rock in your front yard, let alone the world in all its varied possibility. And we certainly haven't figured out a "model" which would let a computer generate new and valid data that expands its understanding of the world beyond its inputs, so self-training is a non-starter for LLMs. What the LLM is "understanding", and what it is reinforced to "understand" is not the world but the format of texts, and while it may get very good at understanding the format of texts, that isn't equivalent to an understanding of the world.

tazjin 3y ago
The world on our plane of existence absolutely is exhaustible, just on a much, much larger scale. Doesn't mean that the process is fundamentally different, and for the human perspective there might be diminishing returns.
deleted 3y ago
[deleted]
famouswaffles 3y ago
>The sum of all human artifacts ever made (or yet to be made) doesn't exhaust the description of a rock in your front yard, let alone the world in all its varied possibility. No human or creature we know of has a "true" world model so this is irrelevant. You don't experience the "real world". You experience a tiny slice of it, a few senses that is further slimmed down and even fabricated at parts. To the bird who can intuitively sense and use electromagnetic waves for motion and guidance, your model of the world is fundamentally incomplete. There is a projection of the world in text. Moreover training on additional modalities is trivial for a transformer. That's all that matters.
- lsy 3y ago
  That's the difference though. 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. To a neural network there is no distinction. The closest the entire dynamic comes is the very basic annotation of RLHF which itself is done by an external human who is providing the value judgment, but even that is absent once training is over. Despite not having the bird's sense for electromagnetic waves, I have an understanding that they are there, because humans saw behavior they couldn't describe and investigated, in a back-and-forth with a world that has some capacity to disprove hypotheses. Additional modalities are really just reducible to more kinds of text. That still doesn't exhaust the world, and unless a machine has some ability to integrate new data in real time alongside a meaningful commitment and accountability to the world as a world, it won't be able to cope with the real world in a way that would constitute genuine intelligence.
  - famouswaffles 3y ago
    >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 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 https://arxiv.org/abs/2305.14975 Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334 https://arxiv.org/abs/2205.14334 Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221 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 https://arxiv.org/abs/2310.06824 Your argument seems to boil down to "they can't perform experiments" but that isn't true either.
kubiton 3y ago
What if we are just the result of a ml network with a model of the world?
- user_named 3y ago
  We're not.
pizza 3y ago
Kant would like a word with you about your point on whether people themselves understand the world and not just the format of their perceptions... :) I think if you're going to be strict about this, you have to defend against the point of view that the same 'ding an sich' problem applies to both LLMs and people. And also whether if you had a limit sequence of KL divergences, one from a person's POV of the world, and one from an LLM's POV of texts, what it is about how a person approaches better grasp of reality - and likewise their KL divergence approaches 0, in some sense implying that their world model is becoming the same as the distribution of the world - that can only apply to people. It seems possible to me that there is probably a great deal of lurking anthropocentrism that humanity is going to start noticing more and more in ourselves in the coming years, probably in both the direction of AI and the direction of other animals as we start to understand both better

by lsy 3y ago

tazjin 3y ago

The world on our plane of existence absolutely is exhaustible, just on a much, much larger scale. Doesn't mean that the process is fundamentally different, and for the human perspective there might be diminishing returns.

deleted 3y ago

[deleted]

famouswaffles 3y ago

>The sum of all human artifacts ever made (or yet to be made) doesn't exhaust the description of a rock in your front yard, let alone the world in all its varied possibility. No human or creature we know of has a "true" world model so this is irrelevant. You don't experience the "real world". You experience a tiny slice of it, a few senses that is further slimmed down and even fabricated at parts. To the bird who can intuitively sense and use electromagnetic waves for motion and guidance, your model of the world is fundamentally incomplete. There is a projection of the world in text. Moreover training on additional modalities is trivial for a transformer. That's all that matters.

lsy 3y ago
That's the difference though. 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. To a neural network there is no distinction. The closest the entire dynamic comes is the very basic annotation of RLHF which itself is done by an external human who is providing the value judgment, but even that is absent once training is over. Despite not having the bird's sense for electromagnetic waves, I have an understanding that they are there, because humans saw behavior they couldn't describe and investigated, in a back-and-forth with a world that has some capacity to disprove hypotheses. Additional modalities are really just reducible to more kinds of text. That still doesn't exhaust the world, and unless a machine has some ability to integrate new data in real time alongside a meaningful commitment and accountability to the world as a world, it won't be able to cope with the real world in a way that would constitute genuine intelligence.
- famouswaffles 3y ago
  >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 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 https://arxiv.org/abs/2305.14975 Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334 https://arxiv.org/abs/2205.14334 Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221 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 https://arxiv.org/abs/2310.06824 Your argument seems to boil down to "they can't perform experiments" but that isn't true either.

kubiton 3y ago

What if we are just the result of a ml network with a model of the world?

user_named 3y ago
We're not.

pizza 3y ago

Kant would like a word with you about your point on whether people themselves understand the world and not just the format of their perceptions... :) I think if you're going to be strict about this, you have to defend against the point of view that the same 'ding an sich' problem applies to both LLMs and people. And also whether if you had a limit sequence of KL divergences, one from a person's POV of the world, and one from an LLM's POV of texts, what it is about how a person approaches better grasp of reality - and likewise their KL divergence approaches 0, in some sense implying that their world model is becoming the same as the distribution of the world - that can only apply to people. It seems possible to me that there is probably a great deal of lurking anthropocentrism that humanity is going to start noticing more and more in ourselves in the coming years, probably in both the direction of AI and the direction of other animals as we start to understand both better