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Comment by ccozan | Hacker News Reader

GPT and human brain ( at least the language / speech part ) have nothing in common. We, as humans, do not use language in a generative way, is derived from a higher or very low level of abstraction ( intentions, emotions, etc ) and is explictly use for communicating something. Even this text is based on previous knowledge, saved in an abstract way, and while writing this I must follow the synthax of the language or writing the right order otherwise, you , the person who reads this, will not understand what I mean. While GPT can generate the same text, it does not have a motivation and has no need to communicate ( while I just wanted to feel good by bringing some contribution on HN ).

So yes, very different architecture.

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> and while writing this I must follow the synthax of the language or writing the right order otherwise

A good example that is not, word randomised order and kombination with Mrs Spelling and fonetic spel-ing prevent ye knot that which I wrote you to komprehend.

(My apologies to non-native speakers of English; if someone did that to me in German I'd have no clue what was meant).

A better point is that GPT-3's training set is more tokens than the number of times an average human synapse fires in a lifetime, squeezed into a network with about 3 orders of magnitude fewer parameters than the human brain has synapses.

It's wrong to model AI as anything like natural intelligence, but if someone insists, my go-to comparison (with an equivalent for image generators) is this: "Imagine someone made a rat immortal, then made it browse the web for 50,000 years. It's still a rat, despite being very well-trained."

> (My apologies to non-native speakers of English; if someone did that to me in German I'd have no clue what was meant).

At least for me it's perfectly understandable (except the "Mrs" part). This reminds of those "did you know you can flip characters randomly and our brain can still understand the text" copypastas that can be found everywhere. I think it's probably quite similar for word order: As long as your sentence structure is not extremely complicated, you can probably get away with changing it any way you like. Just like nobody has issues understanding Yoda in Star Wars.

Although I think there are some limits to changing word order - I can imagine complicated legal documents might get impossible to decipher if you start randomizing word order.

These are conceptual "differences" that don't actually explain the mechanics of what's going on. For all you know "motivation", "intentions", etc. are also just GPT-like subsystems, in which case the underlying mechanics are not as different as you imply.

If it were gpt-like sub systems, humans would be emitting MWs of power instead of the 100W now.

Whatever humans have it is many orders of magnitude better…

That's the hardware it runs on, not the software architecture of GPT. I could equally say that transistors are faster than synapses by the same ratio that marathon runners are faster than continental drift.

Or biology evolved a better way to do the same or similar enough computation that we simply haven't yet discovered.

Emotion is just "spiritual" word for a utility function. Or terminal goal to be more precise.

It seems to me that a lot of everyday communication is rather statistical in nature. We don’t necessarily think deeply about each word choice but instead fall back on well worn patterns and habits. We can be more deliberate about how we compose our sentences but most situations don’t call for it. It makes me wonder if we don’t all have a generative language model embedded in our brains that serves up the most likely next set of words based on our current internal state.

> GPT and human brain have nothing in common

Here we go again. They must have something in common, because for about 90% of the tasks the language model agrees with humans, even on novel tasks.

> We, as humans, do not use language in a generative way

Oh, do you want to say we are only doing classification from a short list of classes and don't generate open ended language? Weird, I speak novel word combinations all the time.

No, what is meant is that the next word I speak/write after a current word are not based on a statistical model, but on a world model which includes a language structure based on a defined syntax and cultural variaty. I actually mean what I say while the ChatGPT just parrots around weights and produces an output based purely on statistics. There is zere modeling which translates into real world ( what normally we call "understanding" and "experience" ).

As was said, a different architecture.

Oh, I see. Then I agree with you, an isolated model can't do any world modelling on its own. No matter how large it is, the real world is more complex.

It might be connected to the world, of course. And it might even use toys such as simulators, code execution, math verification and fact checking to further ground itself. I was thinking about the second scenario.

Ok top of it not having "motivation" to communicate, it has literally nothing to be communicated in the first place.

That's the key difference. We use language to express conceptualizations. We have some kind of abstract model somewhere that we are translating.

Maybe it isn't a cohesive model either. All I can say for certain is that - whatever it is - we are expressing it.

GPT does not express. It parrots. There is no conceptualization.

The more experience I get, the more I wonder if this is really the case for us. We certainly have some kind of abstract model in our heads when thinking deeply about a problem. But in many settings - in a work meeting, or socially with friends - I think it is a much more automatic process. The satisfaction you get when saying the right thing, the dread when you say something stupid: It is just like playing a game. Maybe the old philosophical concept of society as merely "language games" is correct after all. A bit silly but I find the thought makes annoying meetings a bit more bearable.

But you are of course right with GPT, it has no inner life and only parrots. It completely lacks something like an inner state, an existence outside of the brief moment it is invoked, or anything like reflection. Reminds me of the novel "Blindsight" (which I actually haven't read yet, but heard good things about!) where there are beings that are intelligent, but not conscious.

Intelligent but not conscious would still be a few steps ahead of GPT.

We can take a concept and refactor it symbolically. GPT can't do that. All it does is find symbols that are semantically close to other symbols.

I’m not sure that those two processes are as distinct as you believe them to be.

You seem very sure they aren't, yet you have no evidence apart from your own belief that you might be correct.

That's circular reasoning.

Yup.

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