Okay that’s a good point. LLMs, without retraining, are limited in the overall amount of complexity they can successfully navigate.
Sort of like a human who isn’t allowed to sleep, in my opinion. A human may be capable of designing an airplane, but not if the human never sleeps, because the complexity is beyond what a human can do in a single day without becoming exhausted and producing errors.
Do you believe that a series of LLMs, with each LLM being trained on the previous LLM’s training data plus the “input/output completions” that the previous iteration performed, would be a general intelligence?
If I sound naive it is because I am trying to apply Occam’s Razor to my own thinking, and minimize the conversation to the absolute minimum necessary set of involvements to move it forward. I’ll consider anything you ask me to, but so far I haven’t seen a reason to involve consciousness in questions of general intelligence. Do you think they are linked?
By the way, if you have a better definition of “general intelligence” than whatever definition was implied by my original challenge, I’m all ears.
It’s more than being limited in the overall complexity. The locked node weights mean that the LLM is fully deterministic…that is, it has no will or goals, no opinion, no sense of self/sense of the environment/sense of the separation between self/environment. It has no comprehension.
Iterative training cycles are already used with LLMs and don’t solve any of those issues.
From the standpoint of psychology, there’s not a wholly agreed upon definition for ‘intelligence’ but most working definitions require the ability to learn from experience, the ability to recognize problems and to generalize and adapt that experience to solve the problem.
Theoretically, if an LLM had “intelligence,” you could ask it about a problem that was completely dereferenced in the training data. An intelligent LLM would be able to comprehend that problem, generalize it to a level that it could relate to some previous experience, then use details about that prior experience to come up with potential solutions to the new problem. LLMs can’t achieve any of those things individually, never mind all together. If someone pulled that off, it wouldn’t convince me their model was worth the level of concern you articulated earlier, but it would get my attention and would be something I’d watch pretty closely.
So you’re assuming determinism is incompatible with consciousness now? Comprehension? I might be “naive about the nature of consciousness” but you’re gullible about it if you think you know those things.
But at least you’ve made a definite claim now about a thing which an LLM cannot do, which is:
Theoretically, if an LLM had “intelligence,” you could ask it about a problem that was completely dereferenced in the training data.
That brings me back to the original challenge: can you articulate such a problem? We can experiment with ChatGPT and see how it handles it.
Okay that’s a good point. LLMs, without retraining, are limited in the overall amount of complexity they can successfully navigate.
Sort of like a human who isn’t allowed to sleep, in my opinion. A human may be capable of designing an airplane, but not if the human never sleeps, because the complexity is beyond what a human can do in a single day without becoming exhausted and producing errors.
Do you believe that a series of LLMs, with each LLM being trained on the previous LLM’s training data plus the “input/output completions” that the previous iteration performed, would be a general intelligence?
If I sound naive it is because I am trying to apply Occam’s Razor to my own thinking, and minimize the conversation to the absolute minimum necessary set of involvements to move it forward. I’ll consider anything you ask me to, but so far I haven’t seen a reason to involve consciousness in questions of general intelligence. Do you think they are linked?
By the way, if you have a better definition of “general intelligence” than whatever definition was implied by my original challenge, I’m all ears.
It’s more than being limited in the overall complexity. The locked node weights mean that the LLM is fully deterministic…that is, it has no will or goals, no opinion, no sense of self/sense of the environment/sense of the separation between self/environment. It has no comprehension.
Iterative training cycles are already used with LLMs and don’t solve any of those issues.
From the standpoint of psychology, there’s not a wholly agreed upon definition for ‘intelligence’ but most working definitions require the ability to learn from experience, the ability to recognize problems and to generalize and adapt that experience to solve the problem.
Theoretically, if an LLM had “intelligence,” you could ask it about a problem that was completely dereferenced in the training data. An intelligent LLM would be able to comprehend that problem, generalize it to a level that it could relate to some previous experience, then use details about that prior experience to come up with potential solutions to the new problem. LLMs can’t achieve any of those things individually, never mind all together. If someone pulled that off, it wouldn’t convince me their model was worth the level of concern you articulated earlier, but it would get my attention and would be something I’d watch pretty closely.
So you’re assuming determinism is incompatible with consciousness now? Comprehension? I might be “naive about the nature of consciousness” but you’re gullible about it if you think you know those things.
But at least you’ve made a definite claim now about a thing which an LLM cannot do, which is:
That brings me back to the original challenge: can you articulate such a problem? We can experiment with ChatGPT and see how it handles it.