Well, the LLM does briefly ‘think’ about apples in that it activates its ‘thought’ areas relating to apples (the token repressing apples in its system). Right now, an llm’s internal experience is based on its previous training and the current prompt while it’s running. Our brains are always on and circulating thoughts, so of course that’s a very different concept of experience. But you can bet there are people working on building an ai system (with llm components) that works that way too. The line will get increasingly blurred. Or brain processing is just an organic based statistical model with complex state management and chemical based timing control.
You misunderstand. The outcome of asking an LLM to think about an apple is the token ‘Okay’. It probably doesn’t get very far into even what you claim is ‘thought’ about apples, because when someone says the phrase “Think about X”, the immediate response is almost always ‘Okay’ and never anything about whatever ‘X’ is. That is the sum total of its objective. It does not perform a facsimile of human thought; it performs an analysis of what the most likely next token would be, given what text existed before it. It imitates human output without any of the behavior or thought processes that lead up to that output in humans. There is no model of how the world works. There is no theory of mind. There is only how words are related to each other with no ‘understanding’. It’s very good at outputting reasonable text, and even drawing inferences based on word relations, but anthropomorphizing LLMs is a path that leads to exactly the sort of conclusion that the original comic is mocking.
Asking an LLM if it is alive does not cause the LLM to ponder the possibility of whether or not it is alive. It causes the LLM to output the response most similar to its training data, and nothing more. It is incapable of pondering its own existence, because that isn’t how it works.
Yes, our brains are actually an immensely complex neural network, but beyond that the structure is so ridiculously different that it’s closer to comparing apples to the concept of justice than comparing apples to oranges.
I’m well aware of how llms work. And I’m pretty sure the apple part in the prompt would trigger significant activity in the areas related to apples. It’s obviously not a thought about apples the way a human would. The complexity and the structure of a human brain is very different. But the llm does have a model of how the world works from its token relationship perspective. That’s what it’s doing - following a model. It’s nothing like human thought, but it’s really just a matter of degrees. Sure apples to justice is a good description. And t doesn’t ‘ponder’ because we don’t feedback continuously in a typical llm setup, although I suspect that’s coming. But what we’re doing with llms is a basis of thought. I see no fundamental difference except scales between current llms and human brains.
Well, the LLM does briefly ‘think’ about apples in that it activates its ‘thought’ areas relating to apples (the token repressing apples in its system). Right now, an llm’s internal experience is based on its previous training and the current prompt while it’s running. Our brains are always on and circulating thoughts, so of course that’s a very different concept of experience. But you can bet there are people working on building an ai system (with llm components) that works that way too. The line will get increasingly blurred. Or brain processing is just an organic based statistical model with complex state management and chemical based timing control.
You misunderstand. The outcome of asking an LLM to think about an apple is the token ‘Okay’. It probably doesn’t get very far into even what you claim is ‘thought’ about apples, because when someone says the phrase “Think about X”, the immediate response is almost always ‘Okay’ and never anything about whatever ‘X’ is. That is the sum total of its objective. It does not perform a facsimile of human thought; it performs an analysis of what the most likely next token would be, given what text existed before it. It imitates human output without any of the behavior or thought processes that lead up to that output in humans. There is no model of how the world works. There is no theory of mind. There is only how words are related to each other with no ‘understanding’. It’s very good at outputting reasonable text, and even drawing inferences based on word relations, but anthropomorphizing LLMs is a path that leads to exactly the sort of conclusion that the original comic is mocking.
Asking an LLM if it is alive does not cause the LLM to ponder the possibility of whether or not it is alive. It causes the LLM to output the response most similar to its training data, and nothing more. It is incapable of pondering its own existence, because that isn’t how it works.
Yes, our brains are actually an immensely complex neural network, but beyond that the structure is so ridiculously different that it’s closer to comparing apples to the concept of justice than comparing apples to oranges.
I’m well aware of how llms work. And I’m pretty sure the apple part in the prompt would trigger significant activity in the areas related to apples. It’s obviously not a thought about apples the way a human would. The complexity and the structure of a human brain is very different. But the llm does have a model of how the world works from its token relationship perspective. That’s what it’s doing - following a model. It’s nothing like human thought, but it’s really just a matter of degrees. Sure apples to justice is a good description. And t doesn’t ‘ponder’ because we don’t feedback continuously in a typical llm setup, although I suspect that’s coming. But what we’re doing with llms is a basis of thought. I see no fundamental difference except scales between current llms and human brains.