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So just train a GPT on sensory input, etc. His prediction #4 rings false to me. And this popular insistence that GPT has no 'world model' is also false IMHO.

So just train a GPT on sensory input, etc. His prediction #4 rings false to me. And this popular insistence that GPT has no 'world model' is also false IMHO. If a GPT is trained on real-world sensory data, it will develop a spacio-temporal 'world model', almost by definition. LLMs are trained on human text. Their 'world model' is the world encoded in that text, rather than as sounds and retina images, etc, and so it's inconsistent, incomplete, and 'unreal' in a way which is easy to expose. But there is a 'world model' of sorts there.

YeGoblynQueenne 4y ago
>> If a GPT is trained on real-world sensory data, it will develop a spacio-temporal 'world model', almost by definition. Or, most likely, it will develop a model of the data it was trained on, and not the world this data came from. I'm also curious what you mean by "real-world sensory data". So far, deep neural net models have been trained mainly (say 80%) on things like text, images, time series... and that's about it really. What is "real-world sensory data" in that context?
- jacknews 4y ago
  I think, therefore I am. What is your 'world model'? It is, ultimately, associations between sensory inputs, and outputs, and sequences of them. Which, as Descartes pointed out, could all be fake, and maybe not from any real world at all.
  - YeGoblynQueenne 4y ago
    I don't understand. What does all this mean? I just asked what you mean by "real-world sensor data". What does Descartes have to do with it?
    - jacknews 4y ago
      "Or, most likely, it will develop a model of the data it was trained on, and not the world this data came from." I mean the point is what is the difference? Is your brain trained on 'the real world', or on your senses (data) of the real world? Descartes argued that you can't tell if there's a real world at all. By 'real-world sensor data' I mean that the models can be trained on sensor data from the real world (video, audio, feedback from motor outputs, etc), rather than on text, which is only abstractly related to the real world. I believe this is called the token-grounding problem, and goes back to Searle's Chinese Room thought experiment.

YeGoblynQueenne 4y ago

>> If a GPT is trained on real-world sensory data, it will develop a spacio-temporal 'world model', almost by definition. Or, most likely, it will develop a model of the data it was trained on, and not the world this data came from. I'm also curious what you mean by "real-world sensory data". So far, deep neural net models have been trained mainly (say 80%) on things like text, images, time series... and that's about it really. What is "real-world sensory data" in that context?

jacknews 4y ago
I think, therefore I am. What is your 'world model'? It is, ultimately, associations between sensory inputs, and outputs, and sequences of them. Which, as Descartes pointed out, could all be fake, and maybe not from any real world at all.
- YeGoblynQueenne 4y ago
  I don't understand. What does all this mean? I just asked what you mean by "real-world sensor data". What does Descartes have to do with it?
  - jacknews 4y ago
    "Or, most likely, it will develop a model of the data it was trained on, and not the world this data came from." I mean the point is what is the difference? Is your brain trained on 'the real world', or on your senses (data) of the real world? Descartes argued that you can't tell if there's a real world at all. By 'real-world sensor data' I mean that the models can be trained on sensor data from the real world (video, audio, feedback from motor outputs, etc), rather than on text, which is only abstractly related to the real world. I believe this is called the token-grounding problem, and goes back to Searle's Chinese Room thought experiment.