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Definitely a given, it isn't like AI has an actual brain capable of resolving and forming new connections. The LLM and human brains is that LLMs are interactive

Definitely a given, it isn't like AI has an actual brain capable of resolving and forming new connections. The LLM and human brains is that LLMs are interactive compendiums and our brains organize and sort information that ensures survival as an organism. There is no survival of whether or not LLMs are accurate and a machine wouldn't understand what is good or bad without weighted context. Its good for analyze, process, storing, retrieving and decomposing information. It isn't good at understanding, validating and forming connections between the things it says and what you want of it. It lacks comprehension, it doesn't lack composure.

golol 3y ago
The result in the theorem applies to your brain. Your brain can be modelled as an LLM in the sense of the paper up to arbitrarily small error. The result is a diagonalization argument that is not very relevant for the real world.
- wredue 3y ago
  >your brain can be modelled as an LLM in the sense of the paper The vast majority of people actually writing LLMs don’t claim this, and in fact, actually claim the very opposite: that LLMs do not accurately model a human brain in any capacity. The fact is that science has no clue what happens in the nucleus of a neuron, so claiming that computer scientists must is… well. You fill in the word.
  - golol 3y ago
    Definition 2 (Large Language Model). Let S be a computable seta of all the finite-length strings of alphabet A and (s0, s1, . . .) be an one-to-one enumeration of all the elements in S. A large language model, denoted h, is a function that completes the input string s ∈ S using the function’s predicted tokens h(s), in a finite time. Function h is attained procedurally using a set of training samples of input-completion pairs. For an arbtrarily large duration and an arbitrarily small error with respect to any definition of error you choose, there exists an LLM in the above sense which models the dynamics of your brain with that small error.
breck 3y ago
> capable of resolving and forming new connections > There is no survival of whether or not LLMs are accurate I agree that today's LLMs are still missing important components like these needed for breakout intelligence, but I would not be surprised if researchers discover how to add them (and other important things) within 0-5 years.

golol 3y ago

The result in the theorem applies to your brain. Your brain can be modelled as an LLM in the sense of the paper up to arbitrarily small error. The result is a diagonalization argument that is not very relevant for the real world.

wredue 3y ago
>your brain can be modelled as an LLM in the sense of the paper The vast majority of people actually writing LLMs don’t claim this, and in fact, actually claim the very opposite: that LLMs do not accurately model a human brain in any capacity. The fact is that science has no clue what happens in the nucleus of a neuron, so claiming that computer scientists must is… well. You fill in the word.
- golol 3y ago
  Definition 2 (Large Language Model). Let S be a computable seta of all the finite-length strings of alphabet A and (s0, s1, . . .) be an one-to-one enumeration of all the elements in S. A large language model, denoted h, is a function that completes the input string s ∈ S using the function’s predicted tokens h(s), in a finite time. Function h is attained procedurally using a set of training samples of input-completion pairs. For an arbtrarily large duration and an arbitrarily small error with respect to any definition of error you choose, there exists an LLM in the above sense which models the dynamics of your brain with that small error.

breck 3y ago

> capable of resolving and forming new connections > There is no survival of whether or not LLMs are accurate I agree that today's LLMs are still missing important components like these needed for breakout intelligence, but I would not be surprised if researchers discover how to add them (and other important things) within 0-5 years.