ideonekFeb 4

Apophenia

https://piefed.social/c/fuck_ai/p/1738096/pareidolia

Show threadramble81Feb 4

Seriously the sheer amount of people that equate coherent speech with sentience is mind boggling.

All jokes aside, I have heard some decently educated technical people say “yeah, it’s really creepy that it put a random laugh in what it said” or “it broke the 4th wall when talking”… it’s fucking programmed to do that and you just walked right in to it.

Show threadCannonFodderFeb 4
And people are programmed to talk like that too. It’s just a matter of scale.
Show threadchaogomuFeb 4

The difference is knowledge. You know what an apple is. A LLM does not. It has training data that has the word apple is associated with the words red, green, pie, and doctor.

The model then uses a random number generator to mix those words up a bit, and see if the result looks a bit like the training data, and if it does, the model spits out a sequence of words that may or may not be a sentence, depending on the size and quality of the training data.

At no point is any actual meaning associated with any of the words. The model is just trying to fit different shaped blocks through different shaped holes, and sometimes everything goes through the square hole, and you get hallucinations.

Show threadCannonFodderFeb 4
Our brains just get signals coming in from our nerves that we learn to associate with a concept of the apple. We have years of such training data, and we use more than words to tokenize thoughts, and we have much more sophisticated state / memory; but it’s essentially the same thing, just much much more complex. Our brains produce output that is consistent with its internal models and constantly use feedback to improve those models.
Show threadSparroHawcFeb 5

You can tell a person to think about apples, and the person will think about apples.

You can tell an LLM ‘think about apples’ and the LLM will say ‘Okay’ but it won’t think about apples; it is only saying ‘okay’ because its training data suggests that is the most common response to someone asking someone else to think about apples. LLMs do not have an internal experience. They are statistical models.

Show threadCannonFodder
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.
Feb 5 at 5:25pmWeb
Show threadSparroHawcFeb 6

You misunderstand. The outcome of asking an LLM to think about an apple is the token ‘Okay’. 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.

Show threadCannonFodderFeb 6
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.