In some ways no, because to learn something you have to LEARN that then thats in the training data. But humans can do it continuously and sometimes randomly, and also being without prompted.
If you're a scientist -- and in many cases if you're an engineer, or a philosopher, or even perhaps a theologian -- your job is quite literally to add to humanity's training data.
I'd add that fiction is much more complicated. LLMs can clearly write original fiction, even if they are, as yet, not very good at it. There's an idea (often attributed to John Gardner or Leo Tolstoy) that all stories boil down to one of two scenarios:
So I'd tentatively expect tomorrow's LLMs to write good fiction along those well-trodden paths. I'm less sanguine about their applications in scientific invention and in producing original music.
Are you seriously comparing chips running AI models and human brains now???
Last time I checked the chips are not rewiring themselves like the brain does, nor does even the software rewrite itself, or the model recalibrate itself - anything that could be called "learning", normal daily work for a human brain.
Also, the models are not models of the world, but of our text communication only.
Human brains start by building a model of the physical world, from age zero. Much later, on top of that foundation, more abstract ideas emerge, including language. Text, even later. And all of it on a deep layer of a physical world model.
The LLM has none of that! It has zero depth behind the words it learned. It's like a human learning some strange symbols and the rules governing their appearance. The human will be able to reproduce valid chains of symbols following the learned rules, but they will never have any understanding of those symbols. In the human case, somebody would have to connect those symbols to their world model by telling them the "meaning" in a way they can already use. For the LLM that is not possible, since it doesn't habe such a model to begin with.
How anyone can even entertain the idea of "AGI" based on uncomprehending symbol manipulation, where every symbol has zero depth of a physical world model, only connections to other symbols, is beyond me TBH.
Speaking as someone who thinks the Chinese Room argument is an obvious case of begging the question, GP isn't about that. They're not saying that LLMs don't have world models - they're saying that those world models are not based in physical world and thus cannot properly understand what they talk about.
I don't think that's true anymore, though. All the SOTA models are multimodal now, meaning that they are trained on images and videos as well, not just text; and they do that is precisely because it improves the text output as well, for this exact reason. Already, I don't have to waste time explaining to Claude or Codex what I want on a webpage - I can just sketch a mock-up, or when there's a bug, I take a screenshot and circle the bits that are wrong. But this extends into the ability to reason about real world, as well.
In some ways no, because to learn something you have to LEARN that then thats in the training data. But humans can do it continuously and sometimes randomly, and also being without prompted.
If you're a scientist -- and in many cases if you're an engineer, or a philosopher, or even perhaps a theologian -- your job is quite literally to add to humanity's training data.
I'd add that fiction is much more complicated. LLMs can clearly write original fiction, even if they are, as yet, not very good at it. There's an idea (often attributed to John Gardner or Leo Tolstoy) that all stories boil down to one of two scenarios:
> "A stranger comes to town."
> "A person goes on a journey."
Christopher Booker wrote that there are seven: https://en.wikipedia.org/wiki/The_Seven_Basic_Plots
So I'd tentatively expect tomorrow's LLMs to write good fiction along those well-trodden paths. I'm less sanguine about their applications in scientific invention and in producing original music.
Yes, they can.
Ever heard of creativity?
Are you seriously comparing chips running AI models and human brains now???
Last time I checked the chips are not rewiring themselves like the brain does, nor does even the software rewrite itself, or the model recalibrate itself - anything that could be called "learning", normal daily work for a human brain.
Also, the models are not models of the world, but of our text communication only.
Human brains start by building a model of the physical world, from age zero. Much later, on top of that foundation, more abstract ideas emerge, including language. Text, even later. And all of it on a deep layer of a physical world model.
The LLM has none of that! It has zero depth behind the words it learned. It's like a human learning some strange symbols and the rules governing their appearance. The human will be able to reproduce valid chains of symbols following the learned rules, but they will never have any understanding of those symbols. In the human case, somebody would have to connect those symbols to their world model by telling them the "meaning" in a way they can already use. For the LLM that is not possible, since it doesn't habe such a model to begin with.
How anyone can even entertain the idea of "AGI" based on uncomprehending symbol manipulation, where every symbol has zero depth of a physical world model, only connections to other symbols, is beyond me TBH.
Watch out, you're getting suspiciously close to the Chinese Room argument. And people on here really don't like that argument.
Speaking as someone who thinks the Chinese Room argument is an obvious case of begging the question, GP isn't about that. They're not saying that LLMs don't have world models - they're saying that those world models are not based in physical world and thus cannot properly understand what they talk about.
I don't think that's true anymore, though. All the SOTA models are multimodal now, meaning that they are trained on images and videos as well, not just text; and they do that is precisely because it improves the text output as well, for this exact reason. Already, I don't have to waste time explaining to Claude or Codex what I want on a webpage - I can just sketch a mock-up, or when there's a bug, I take a screenshot and circle the bits that are wrong. But this extends into the ability to reason about real world, as well.
1 reply →