…like what? I thought the consensus was that humans exhibit truly general intelligence. If LLMs require access to very specific tools to solve certain classes of problems, then it’s not clear that they can evolve into a form of general intelligence.
Specifically, which portions of the brain are “very specialized”? I’m not aware of any aspect of the brain that’s as narrowly applied to tasks as the tools LLMs use. For example, there’s no coding module within the brain - the same brain regions you use when programming could be used to perform many, many other tasks.
They are, but I think the keyword is "generalization". Humans do very well when innovation is required, because innovation needs generalized models that can be used to make very specialized predictions and then meta-models that can predict how specialized models relate to each other and cross reference those predictions. We don't learn arithmetic by getting fed terabytes of text like "1+1=2". We only use text to communicate information, but learn the actual logic and concept behind arithmetic, and then we use that generalized model for arithmetic in our reasoning.
I struggle to imagine how much further a purely text based system can be pushed - a system that basically knows that 1+1=2 not because it has built an internal model of arithmetic, but because it estimates that the sequence of `1+1=` is mostly followed by `2`.
They have somewhat an internal model of arithmetic, with lookup tables and separate treatment of digits. I'm conscious you might have seen this already and not interpret it like that, but in case you haven't section 6 on addition in this Anthropic interpretability paper goes into it.
Keep in mind that is a basic level of understanding of what is going on in quite a small model (Claude 3.5 Haiku). We don't know what is happening inside larger models.
…like what? I thought the consensus was that humans exhibit truly general intelligence. If LLMs require access to very specific tools to solve certain classes of problems, then it’s not clear that they can evolve into a form of general intelligence.
What would you call the very specialized portions of our brains?
The brain is not a monolith.
Specifically, which portions of the brain are “very specialized”? I’m not aware of any aspect of the brain that’s as narrowly applied to tasks as the tools LLMs use. For example, there’s no coding module within the brain - the same brain regions you use when programming could be used to perform many, many other tasks.
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They are, but I think the keyword is "generalization". Humans do very well when innovation is required, because innovation needs generalized models that can be used to make very specialized predictions and then meta-models that can predict how specialized models relate to each other and cross reference those predictions. We don't learn arithmetic by getting fed terabytes of text like "1+1=2". We only use text to communicate information, but learn the actual logic and concept behind arithmetic, and then we use that generalized model for arithmetic in our reasoning.
I struggle to imagine how much further a purely text based system can be pushed - a system that basically knows that 1+1=2 not because it has built an internal model of arithmetic, but because it estimates that the sequence of `1+1=` is mostly followed by `2`.
They have somewhat an internal model of arithmetic, with lookup tables and separate treatment of digits. I'm conscious you might have seen this already and not interpret it like that, but in case you haven't section 6 on addition in this Anthropic interpretability paper goes into it.
https://transformer-circuits.pub/2025/attribution-graphs/bio...
Keep in mind that is a basic level of understanding of what is going on in quite a small model (Claude 3.5 Haiku). We don't know what is happening inside larger models.