Benchmarks used to rank AI models are several years old, often sourced from amateur websites, and, experts worry, lending automated systems a dubious sense of authority
what solid proof do we have that humans aren’t doing the same?
Humans are not computers. Brains are not LLMs…
Given a totally reasonable hypothesis (humans =/= computers) and a completely outlandish hypothesis (humans = computers), I would need much more ‘proof’ for the later.
Well, brains are a network of neurons (we can evidentially verify this) trained on … eyes, ears, sense of touch, taste, smell and balance (rewarded by endorphins released by the old brain on certain hardcoded stimuli). LLMs are a network of neurons trained on text and images (rewarded by producing text that mimics input text and some reasoning tests).
It’s not given that this results in the same way of dealing with language, given the wider set of input data for a human, but it’s not given that it doesn’t either.
Humans predict things by assigning meaning to events and things, because in nature, we’re constantly trying to guess what other creatures are planning. An LLM does not hypothesize what your plans are when you communicate to it, it’s just trying to predict the next set of tokens with the greatest reward value. Even if you were to use literal human neurons to build your LLM, you would still have a stochastic parrot.
Humans are not computers. Brains are not LLMs…
Given a totally reasonable hypothesis (humans =/= computers) and a completely outlandish hypothesis (humans = computers), I would need much more ‘proof’ for the later.
Well, brains are a network of neurons (we can evidentially verify this) trained on … eyes, ears, sense of touch, taste, smell and balance (rewarded by endorphins released by the old brain on certain hardcoded stimuli). LLMs are a network of neurons trained on text and images (rewarded by producing text that mimics input text and some reasoning tests).
It’s not given that this results in the same way of dealing with language, given the wider set of input data for a human, but it’s not given that it doesn’t either.
Humans predict things by assigning meaning to events and things, because in nature, we’re constantly trying to guess what other creatures are planning. An LLM does not hypothesize what your plans are when you communicate to it, it’s just trying to predict the next set of tokens with the greatest reward value. Even if you were to use literal human neurons to build your LLM, you would still have a stochastic parrot.