Your brain is also “just” matching inputs to outputs using complex statistics, a huge number of interconnects and clever digital-analog mixed ionic circuitry.
At a super high level, sure. But human brains also have tens of thousands of years (perhaps hundreds of thousands) to develop, so it’s not like a newborn baby is working off a blank slate, there’s a ton of evolutionary circuitry in there that influences things.
That’s why an algorithm that is based on human data will never quite work like a human. That doesn’t mean it’s not intelligent, it just requires a different set of requirements. That’s why I think the Turing test is a bad metric, since an LLM could just find “proper” responses given a bunch of existing conversations without having to reason about the conversation.
Real intelligence, imo, would need to be able to learn to solve puzzles without seeing similar puzzles. That’s more the domain of other “AI” fields like neural networks and machine learning. But each field approaches problems in a different, limited way, so general AI will be quite complicated unless we find a new approach.
Your brain is also “just” matching inputs to outputs using complex statistics, a huge number of interconnects and clever digital-analog mixed ionic circuitry.
At a super high level, sure. But human brains also have tens of thousands of years (perhaps hundreds of thousands) to develop, so it’s not like a newborn baby is working off a blank slate, there’s a ton of evolutionary circuitry in there that influences things.
That’s why an algorithm that is based on human data will never quite work like a human. That doesn’t mean it’s not intelligent, it just requires a different set of requirements. That’s why I think the Turing test is a bad metric, since an LLM could just find “proper” responses given a bunch of existing conversations without having to reason about the conversation.
Real intelligence, imo, would need to be able to learn to solve puzzles without seeing similar puzzles. That’s more the domain of other “AI” fields like neural networks and machine learning. But each field approaches problems in a different, limited way, so general AI will be quite complicated unless we find a new approach.