Don’t get fooled by clever tricks from developers, LLMs are a mathematical function, where it gets the chain of numbers you give it and returns a new chain of numbers. LLMs are 100% predeterministic, programmers purposefully make them choose a random response within a degree of tolerance instead of picking the correct answer.
I saw you making this claim on another comment, this is COMPLETELY different from how humans/animals/plants think. LLMs are incapable of thought, incapable of learning, and incapable of understanding, that’s why they fail dumb tests like “how many Rs in strawberry”, they’re just average machines.
They’re not useless, they’re not intelligent, they’re a tool, you don’t think your calculator is intelligent because it can do math you can’t, and shouldn’t think an LLM is intelligent because it can aggregate texts that you can’t.
All that being said, you’re correct that LLMs do pass the Turing test, but that doesn’t mean what you think it does, it just means they’re very good at pretending to.
I would argue that humans are the same, we just don’t have access to our programming. If we did, and could measure the state of our brains, we would be entirely deterministic, as well.
That’s a very Newtonian way to look at the world. Even IF that was correct (which is not because of the uncertainty principle), if you go down that road you will get to the conclusion that everything is intelligent even a simple program that chooses an alternate greeting between Hello and Hi can be considered intelligent by that standard.
Yes, I know, and what you’re overlooking is that the uncertainty principle applies to LLM, as well, and even your example alternating algorithm.
That’s why a solid definition of intelligence is necessary, and my own is that the closer the number of relevant, comprehensibly potential responses approaches infinity, the more intelligent it is. On this scale modern AI is not as intelligent as humans, but it’s certainly more intelligent than your alternating greeting.
The uncertainty principle does NOT apply to LLMs and absolutely, unquestionably does NOT apply to my alternating algorithm. You need to understand the difference between “I don’t know” and “It’s unknowable”.
It most certainly does. Do you think that you know the position and state of all the electrons in a computer when a program is executing? It’s unknowable, and checking the status collapses the superposition, changing the measurement. It’s no different from the status of the synapses in our brains. Even your simple “Hi” vs “Hello” program has a non-zero probability of outputting neither, or both expected outputs.
I think that the position and state of every single electron is mostly irrelevant. My alternating greeting can be made with a paper having one side written each greeting and flipping it every time, you also don’t need to know the state of every subatomic particle there, even though there is a possibility that every single electron in that piece of paper suddenly moves away and the vacuum in electrical charge causes a rush of electricity that vaporizes the whole room… Yeah it’s possible, but you’re a dumbass if you think that possibility is worth calculating.
The same is true for a computer, and again you’re mixing up “I can’t possibly know that” with “it’s unknowable”. Knowing the electrical charge at each position of the computer is knowable, knowing the electrical charge at each position of a brain is also knowable, but while knowing that information on a computer allows you to predict its outcome, the same is not true for a brain.
You sound quite sure of yourself, but I believe you are mistaken. The state of the electrons does indeed matter when a program is executing.
What makes you think that we will never be able to predict the outcome of a brain it we had the same knowledge of it as we did of a comparable neural network? You’d have to be a dumbass if you think that the medium matters in knowability of a system. Whether biological or mechanical, every state is possible until it’s measured, and once it is, you can determine exactly how it will function for a short period of time. Complexity does not make something unknowable, only complex, and therefore difficult to know.
Unlike the position and state of subatomic particles in any system, including that of the host of an LLM, which are unknowable.
Don’t get fooled by clever tricks from developers, LLMs are a mathematical function, where it gets the chain of numbers you give it and returns a new chain of numbers. LLMs are 100% predeterministic, programmers purposefully make them choose a random response within a degree of tolerance instead of picking the correct answer.
I saw you making this claim on another comment, this is COMPLETELY different from how humans/animals/plants think. LLMs are incapable of thought, incapable of learning, and incapable of understanding, that’s why they fail dumb tests like “how many Rs in strawberry”, they’re just average machines.
They’re not useless, they’re not intelligent, they’re a tool, you don’t think your calculator is intelligent because it can do math you can’t, and shouldn’t think an LLM is intelligent because it can aggregate texts that you can’t.
All that being said, you’re correct that LLMs do pass the Turing test, but that doesn’t mean what you think it does, it just means they’re very good at pretending to.
I would argue that humans are the same, we just don’t have access to our programming. If we did, and could measure the state of our brains, we would be entirely deterministic, as well.
That’s a very Newtonian way to look at the world. Even IF that was correct (which is not because of the uncertainty principle), if you go down that road you will get to the conclusion that everything is intelligent even a simple program that chooses an alternate greeting between Hello and Hi can be considered intelligent by that standard.
Yes, I know, and what you’re overlooking is that the uncertainty principle applies to LLM, as well, and even your example alternating algorithm.
That’s why a solid definition of intelligence is necessary, and my own is that the closer the number of relevant, comprehensibly potential responses approaches infinity, the more intelligent it is. On this scale modern AI is not as intelligent as humans, but it’s certainly more intelligent than your alternating greeting.
The uncertainty principle does NOT apply to LLMs and absolutely, unquestionably does NOT apply to my alternating algorithm. You need to understand the difference between “I don’t know” and “It’s unknowable”.
It most certainly does. Do you think that you know the position and state of all the electrons in a computer when a program is executing? It’s unknowable, and checking the status collapses the superposition, changing the measurement. It’s no different from the status of the synapses in our brains. Even your simple “Hi” vs “Hello” program has a non-zero probability of outputting neither, or both expected outputs.
I think that the position and state of every single electron is mostly irrelevant. My alternating greeting can be made with a paper having one side written each greeting and flipping it every time, you also don’t need to know the state of every subatomic particle there, even though there is a possibility that every single electron in that piece of paper suddenly moves away and the vacuum in electrical charge causes a rush of electricity that vaporizes the whole room… Yeah it’s possible, but you’re a dumbass if you think that possibility is worth calculating.
The same is true for a computer, and again you’re mixing up “I can’t possibly know that” with “it’s unknowable”. Knowing the electrical charge at each position of the computer is knowable, knowing the electrical charge at each position of a brain is also knowable, but while knowing that information on a computer allows you to predict its outcome, the same is not true for a brain.
You sound quite sure of yourself, but I believe you are mistaken. The state of the electrons does indeed matter when a program is executing.
What makes you think that we will never be able to predict the outcome of a brain it we had the same knowledge of it as we did of a comparable neural network? You’d have to be a dumbass if you think that the medium matters in knowability of a system. Whether biological or mechanical, every state is possible until it’s measured, and once it is, you can determine exactly how it will function for a short period of time. Complexity does not make something unknowable, only complex, and therefore difficult to know.
Unlike the position and state of subatomic particles in any system, including that of the host of an LLM, which are unknowable.