If how exactly it’s implemented matters, regardless of similarity in internal dynamics and states, and there’s an imminent tangibility to it like rain or torque, I think you’re actually talking about a soul.
Behaviorally, analog systems are not substrate dependent. The same second-order differential equations describes RLC circuits, audio resonators and a ball on a spring, for example.
Analog AI chips exist, FWIW.
If you’re looking at complexity theory, I’m pretty sure all physics is in EXPTIME. That’s a strong class, which is why we haven’t solved every problem, but it’s still digital and there’s stronger ones that can come up, like with Presburger arithmetic. Weird fundamentally-continuous problems exist, and there was a pretty significant result in theoretical quantum computer science about it this decade, but actual known physics is very “nice” in a lot of ways. And yes, that includes having numerical approximations to an arbitrary degree of precision.
To be clear, there’s still a lot of problems with the technology, even if it can replace a graphics designer. Your screenshot is a great example of hallucination (particularly the bit about practical situations), or just echoing back a sentiment that was given.
Behaviorally, analog systems are not substrate dependent.
This is partly true, as I already explained at length, since the behavior of any system can be crudely modeled. It’s how LLMs work! But it’s also a non-sequitur.
Modeling what a system can do and doing what a system can do are not the same.
A map isn’t a territory, but there’s no such a thing as a tangible mind you can hold (or there is, and we’re arguing about mysticism, which isn’t really a good use of my time). As far as I can see, it’s all maps.
If how exactly it’s implemented matters, regardless of similarity in internal dynamics and states, and there’s an imminent tangibility to it like rain or torque, I think you’re actually talking about a soul.
Behaviorally, analog systems are not substrate dependent. The same second-order differential equations describes RLC circuits, audio resonators and a ball on a spring, for example.
Analog AI chips exist, FWIW.
If you’re looking at complexity theory, I’m pretty sure all physics is in EXPTIME. That’s a strong class, which is why we haven’t solved every problem, but it’s still digital and there’s stronger ones that can come up, like with Presburger arithmetic. Weird fundamentally-continuous problems exist, and there was a pretty significant result in theoretical quantum computer science about it this decade, but actual known physics is very “nice” in a lot of ways. And yes, that includes having numerical approximations to an arbitrary degree of precision.
To be clear, there’s still a lot of problems with the technology, even if it can replace a graphics designer. Your screenshot is a great example of hallucination (particularly the bit about practical situations), or just echoing back a sentiment that was given.
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This is partly true, as I already explained at length, since the behavior of any system can be crudely modeled. It’s how LLMs work! But it’s also a non-sequitur.
Modeling what a system can do and doing what a system can do are not the same.
What’s the difference?
A map isn’t a territory, but there’s no such a thing as a tangible mind you can hold (or there is, and we’re arguing about mysticism, which isn’t really a good use of my time). As far as I can see, it’s all maps.