LLMs are deterministic simply because computers are at the core deterministic machines. LLMs run on computers and therefore are deterministic. The random number generator is an illusion and an LLM that utilizes it will produce the same illusion of indeterminism. Find the seed and the right generator and you can make an LLM consistently produce the same output from identical input.
Despite determinism, we still do not understand LLMs.
In what sense is this true? We understand the theory of what is happening and we can painstakingly walk through the token generation process and understand it. So in what sense do we not understand LLMs?
Because they encode statistical properties of the training corpus. You might not know why they work but plenty of people know why they work & understand the mechanics of approximating probability distributions w/ parametrized functions to sell it as a panacea for stupidity & the path to an automated & luxurious communist utopia.
No this is false. No one understands. Using big words doesn’t change the fact that you cannot explain for any given input output pair how the LLM arrived at the answer.
Every single academic expert who knows what they are talking about can confirm that we do not understand LLMs. We understand atoms and we know the human brain is made 100 percent out of atoms.we may know how atoms interact and bond and how a neuron works but none of this allows us to understand the brain. In the same way we do not understand LLMs.
Characterizing ML as some statistical approximation or best fit curve is just using an analogy to cover up something we don’t understand. Heck the human brain can practically be characterized by the same analogies. We. Do. Not. Understand. LLMs. Stop pretending that you do.
Nobody knows how LLMs work.
Anybody who claims otherwise is making a false claim.
nobody can how how something that is non-deterministic works - by its pure definition
LLMs are deterministic simply because computers are at the core deterministic machines. LLMs run on computers and therefore are deterministic. The random number generator is an illusion and an LLM that utilizes it will produce the same illusion of indeterminism. Find the seed and the right generator and you can make an LLM consistently produce the same output from identical input.
Despite determinism, we still do not understand LLMs.
In what sense is this true? We understand the theory of what is happening and we can painstakingly walk through the token generation process and understand it. So in what sense do we not understand LLMs?
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I think they meant "Nobody knows why LLMs work."
same thing? The how is not explainable. This is just pedantic. Nobody understands LLMs.
Because they encode statistical properties of the training corpus. You might not know why they work but plenty of people know why they work & understand the mechanics of approximating probability distributions w/ parametrized functions to sell it as a panacea for stupidity & the path to an automated & luxurious communist utopia.
My goodness. Please introduce me to this "plenty of people". I'm in the field, and none of them work with me.
But I can tell you that statistics and parametrized functions have absolutely nothing to do with it. You're way out of your depth my friend.
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No this is false. No one understands. Using big words doesn’t change the fact that you cannot explain for any given input output pair how the LLM arrived at the answer.
Every single academic expert who knows what they are talking about can confirm that we do not understand LLMs. We understand atoms and we know the human brain is made 100 percent out of atoms.we may know how atoms interact and bond and how a neuron works but none of this allows us to understand the brain. In the same way we do not understand LLMs.
Characterizing ML as some statistical approximation or best fit curve is just using an analogy to cover up something we don’t understand. Heck the human brain can practically be characterized by the same analogies. We. Do. Not. Understand. LLMs. Stop pretending that you do.
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