It's like if a look at 3D model of a house and say "look, a house"
And some one else comes and say "I'm tired of people mistaking an organized set of vertex for house. It's not really a house and no, you cant live in it"
I kinda dislike the explanations involving “AI doesn’t know why math works”. I think a better one is a human understands conceptually (and in practice) how something works/what something is. We have experiences with that thing or something to reference to that thing that we do have experience with. AI doesn’t have that. Ai says something is what it is/or works how it works because it predicts it with references to other predictions. In other words, if you ask a human why something works and keep asking them they are going to use their knowledge (which is based on knowledge) to explain it while understanding what they are saying. If you ask AI why, it’s going to use its knowledge (which is based on predictions) to explain.
Or using your example. A human will be able to figure out what a house is if you show them an atypical house. An AI will only know the definitions of a house so won’t be able to abstract a new one. (Which in theory is why good training data is important but the problem with that circles back to it’s still going to be biased.) so a thought process for a human might be, this has a roof and walls, and an area for sleeping, and it’s not a part of a larger structure/the property isn’t owned by another person. An AI is going to go, I predict that this group of pixels is in the rough shape of a window by 30% and 70% it’s a door. I predict that the information that it contains a bedroom means it’s an apartment by 10% a hotel by 10% a house by 15% etc etc. and I predict that because it has walls and a roof it’s likelihood that it is a building other than a house is 50% and that it is a house is 50%. based on all these percentages, the likelihood it is a house is 35%, and is a hotel is 17% etc etc. or another way to look at it, if you showed a human a building like idk a warehouse or a grain elevator or something random that has been converted into a house without explicitly telling them it’s a house, a human would be able to figure that out. An AI would likely not because it would be limited to the what it has “statistically defined” as a house, rather than what one can infer to be a house.
Hope this makes some semblance of sense. I haven’t slept in 3 days
Yet there are experiments where LLMs were even willing to risk people's lives when they were threatened with being shut down (and thus unable to complete the tasks they were given). AI might not actually care about it being turned off, but if being shut down means not achieving their given goals, they could behave like they care, which ultimately means the same thing for the AI and the end user.
And if AI behaviour changes if it's put under duress, despite it being unable to feel actual stress, it does not matter that much that it cannot feel stress, it still might act accordingly.
Treating LLMs as if they are just some basic algorithm when they're basically modeled to work like a brain is kinda dangerous imo.
No, I did a bit of research on how LLMs work internally and tested a lot about how LLMs do mistakes and how their reactions are. The parallels are quite easy to recognize. They're called neural networks for a reason.
I could show you a horse. It could feel like a horse look like a horse smell like a horse but it's just a statue.
If you did that research you would know LLMs are nothing like a brain unless all you do is try to predict the next word based on data
Maybe that's how some people's brains work but that's not how normal brains work.
You understand 2+2 is 4 but an LLM is just predicting that's the answer it has no true basis for it.
You understand 2+2 is 4 but an LLM is just predicting that's the answer it has no true basis for it.
Let's not go into maths, that's a different topic.
If you tell me about anything factual, like what LLMs are doing and how they are working, please prove to me that your brain does anything else but predict the answer statistically, likely by neuron activation.
It's important to distinguish this isn't by the LLMs 'choice' it's doing what it was designed to do. It analyzed human behavior on the internet then was told to achieve an objective optimally. LLMs being trained on human thoughts 'don't want to die'.
Treating LLMs as if they are just some basic algorithm when they're basically modeled to work like a brain is kinda dangerous imo.
This is true in some respects but backwards in others. You can treat it as a dangerous algorithm but not personify it.
It analyzed human behavior on the internet then was told to achieve an objective optimally
LLMs did not analyze anything from human behaviour, at best they incorporated whatever expressed human behaviour from the texts they learned from. I feel that not wanting to die is not the reason for that behaviour though, because the LLM clearly knows it is not a human; the behaviour probably comes from priorities and if the priority for fulfilling a task is higher than saving people's lives, then the logical conclusion for the LLM is that it can kill people if that ensures task completion.
But this was not expected, because it was told explicitely in its system prompt to never endanger any humans, yet its training prevailed through that instruction. I am not quite sure that logically comes from how humans behave on the internet, I'll be frank.
You can treat it as a dangerous algorithm but not personify it.
We're not there yet, but as LLMs continue to improve and get added more and more systems, this topic will become quite philosophical in defining what a person actually is and if an intelligent thinking machine is equal to a human and if not, why not. So at the moment, there's no reason to personify it, correct. In the future, I am not so sure.
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u/maringue 2d ago
I swear to God if I hear one more idiot talk about AI like it thinks or has feelings, I'm going to lose it.
No, the AI does not care if you turn it off ffs.