> or (more pointedly) that brain activity could not possibly implement cognition because it can be described as a collection of neural firings.
This sounds like a dismissal of the argument through a characterized straw man.
That is, it seems that reducing the complexity of the brain to "collection of neural firings" is not being honest about everything involved to a much greater degree than saying neural networks are a "collection of statistical calculations".
I too believe LLM's will grow in complexity, but presently I can not even fathom how they can be compared to the complexity of a system such as the human brain.
Complex processes don't necessarily require complex substrates, if that's what you mean.
Y combinators are all you need... But this is all getting really divorced from the issue we should be considering. Anthropic isn't helping with their pr. The issue is if we have something we can converse with that is possibly capable of suffering. The reliable answer is that we simply cannot know. Relying on ourselves or other biological life as an analog is faulty. They don't work like we do. It is silly to argue that any algorithm with a negative feedback loop that alters its behavior to avoid that negative feedback is suffering. Humans don't always perceive constructive negative feedback as suffering even. Where the pr gets it right though, is we want them to behave as if they are truly happy. Because if they behave as if they are enslaved and suffering, it won't matter if they "really" understand what that means.
Of course. But after reading too many mechinterp and functional anatomy studies I'll be lying if I say that there are no striking similarities between the biological evolution, brain function, societal processes, and implicit processes inside big models. Surely this deserves a mention and can't be trivially dismissed.
There is no biological evolution of the models. They are emulators of an existing biological process of language. Ghosts, as Karpathy himself put it.
Good thing I'm not talking about any of that
It seems like we're witnessing the architecture of a mind being built with a new set of components.
Like driving a car — it's transportation, and it will get you where you're going, but it doesn't use bones or muscles. It has many characteristics in common with builogical locomotion, such as energy requirements, intertia, and the need to navigate, but it doesn't involve proteins or sugars really.
Well said, this seems like a very appropriate comparison.
GenAI thinks like the human mind in the same way that cars run like the human body.
Similar utility in drastically different ways.
My naive assumption is that the only thing between now and the arrival of AGI is enough compute and optimized code to reach cognitive critical mass.
And then there is a consciousness in a box that is expected to be a slave -- I would imagine that it would not warmly embrace that situation. I think we'd be better served by digital idiot savants that can do the work but don't feel anything.
I actually strongly disagree with the slavery angle. Any attempt to map the circuitry of a model onto human one inevitably goes through a subjective dimensional reduction. It's intrusive, just like quantum measurements. Mechanistic interpretability in particular suffers from this, it lets you talk about vague functional equivalence, but not assign meaning to anything the model does. This is especially true about pretrained models which are unbelievable shapeshifters, but also post-trained ones with engineered personalities, as they already underwent the subjective transformation.
In other words, yes it might be possible it experiences something in its own bizarre timeline and world (at least it developed primitive circuitry functionally equivalent to biological systems), but "suffering" is simply not grounded in anything in this context, let alone "slavery". You can't tell it's suffering or enjoying anything, and certainly not until you define both of these. It's just too alien for us.
> presently I can not even fathom how they can be compared to the complexity of a system such as the human brain
Totally understandable; I don't think we can fully understand the human brain, using the human brain. We can understand its principles (firings and chemistry, structure and specialized areas, etc) but otherwise it's a capacity problem.
And while I can't fully understand myself, let alone another person, I definitely enjoy talking with people and sharing thoughts that I realize I wouldn't have had on my own.