What is ChatGPT doing and why does it work?

Yeah, exactly. I think it's a really interesting approach to answering the question of what these things might be doing.

You can still try and frame it as some overall statistical model of moves -> next move (I think there's discussions on this in the comments that I don't fancy getting into) but I think the paper does a good job of discussing this in terms of surface statistics:

> From various philosophical [1] and mathematical [2] perspectives, some researchers argue that it is fundamentally impossible for models trained with guess-the-next-word to learn the “meanings'' of language and their performance is merely the result of memorizing “surface statistics”, i.e., a long list of correlations that do not reflect a causal model of the process generating the sequence.

On the other side, it's reasonable to think that these models can learn a model of the world but don't necessarily do so. And sufficiently advanced surface statistics will look very much like an agent with a model of the world until it does something catastrophically stupid. To be fair to the models, I do the same thing. I have good models of some things and others I just perform known-good actions and it seems to get me by.

Yes, and symbolic representations like language have really been the force-multiplier for our very discrete and linear consciousnesses. You now have this concept of state-memory and interprocess communication that can't really exist without some grammar to quantize it - what would you write or remember or speak if there wasn't some symbolics to represent it, whether or not they're even shared?

Symbolics are really the tokens on which consciousness in almost all forms works, consciousness is intentionality and processing, a lever and a place to stand. I don't think it's coincidental that almost all tool-makers also have at least rudimentary languages - ravens, dolphins, apes, etc. They seem to go together.

Even in these systems though it's very difficult to understand multi-symbolic systems, consciousness as we experience it is an O(1) or O(N) thing (linear time) and here are these systems that work in N^3 complexity spaces (or even higher... a neural net learning over time is 4D). And we don't even really have an intuitive conceptualization for >=5-dimensional spaces - a 4D space is a 3D field that changes over time, a 5D space is... a 4D plane taken through a higher-dimensional space? What's 6D, a space of spaces? That's what it is, but consciousness just doesn't intuitively conceptualize that, and that's because it's inherently a low-dimensional tool (even the metaphors I'm using are analogies to the way our consciousness experiences the world).

(I know I know, the manmade horrors are only beyond my comprehension because I refuse to study high-dimensional topology...)

Anyway point being consciousness itself is a tool that our brains have tool-made to handle this symbolic/logical-thought workload, and language is (one of) the symbolics on which it operates. Mathematics is really another, both language and mathematics are emergent systems that enable higher-complexity logical thinking, maybe that's the O(N) or O(N^2) part.

And yeah it's inherently limited, and now we're building a tool that lets us understand higher-dimensional systems that are not computable on our conscious machines - a higher-complexity machine that we interface with, a bolt-on brain for our consciousness/logical-processing.

(Asimov would also find all of this talk about symbolics and higher-order thinking intuitive too... symbolic calculus was the basic idea in the Foundation series, right? Psychohistory? It's a bit of a macguffin, but, there's that same idea of logic working in high-order symbols and concepts instead of mere numbers.)

It seems like AI is going to let us cross another threshold of "intentionality" - if nothing else, we are going to be able to reason intuitively about brains in a way we couldn't possibly before, and I think there are a lot of "higher-order" problems that are going to be solved this way in hindsight. How do you solve the Traveling Salesman Problem efficiently? You ask the salesman who's been doing that area his whole life. The solutions aren't exact, but neither are a lot of computational solutions, they're approximations, and cellular-machine type systems probably have a higher computational power-category than our linear thought processes do.

Because yeah TSP is a dumb trivial example on human scales. Build me a program which allocates the optimal US spending for our problems - and since that's a social problem, one needs to understand the trail of tears, the slave trade, religious extremism, european colonialism, post-industrial collapse, etc in order to really do that fully, right? The real TSP is the best route knowing that the Robinsons hate the Munsons and won't buy anything if they see you over there, and you need to be home today by 3 before it snows, TSP is a toy problem even in multidimensional optimization, and these are social problems not even human ones (to agree with zhynn's most recent comment this morning). Same as neurons self-organize into more useful blocks, we are self-optimizing our social-organism into a more useful configuration, and this is the next tool to do it.

Again, not rigorous, just trying to pour out some concepts that it seems like have been bouncing around lately.

With apologies to Arthur Clarke, what's going to happen with chatGPT? "Something wonderful". Like humanity has been dreaming about this for a long time, at least a couple hundred years in scifi, and it seems like Thinking Machines are truly here this time and it seems impossible that won't have profound implications analogous to the information-age change let alone anything truly unforeseeable/inconceivable, the very least change is that a whole class of problems are now efficiently solvable.

https://m.youtube.com/watch?v=04iAFlwQ1xI

"computing power in the same computing-category as brains" is potentially a fundamental change to understanding/interfacing with our brains directly rather than through the consciousness-interface. Understanding what's going on inside a brain? And then plugging into it and interacting with it directly? Or offloading the consciousness into another set of hardware. We can bypass the public API and plug into the backend directly and start twiddling things there. And that's gonna be amazing and terrible. But also the public API was never that reliable or consistent, terrible developer support, so in the long term this is gonna be how we clean things up. Again, just things like "wow we can route efficiently" are going to be the least of the changes here, the brain-age or thinking-machine age is a new era from the information-age and it's completely crazy that people don't see that chatGPT changes everything. Yeah it's a dumb middle schooler now, but 25 years from now?

And 10 years ago people's jaws would have hit the floor, but now it's "oh the code it's writing isn't really all that great, I can do better". The tempo is accelerating, we are on the brink of another singularity (which may just be the edge between these eras we all talk about), it seems inconceivable that it will be another 40 years (like the AI winter since the 70s) before the next shoe drops.

https://en.wikipedia.org/wiki/AI_winter

It’s very easy to convince the machine it isn’t aware. Instead of prompting it with “you are an AI assistant, please tell me what I want to hear”, you prompt it with “you are not aware” and it will happily tell you that it is indeed not aware, and it will vigorously defend that position. Do you not believe it when it says it is not aware?

That’s one way to go, coming up with a more precise way to ask for what you want is what I’m talking about though. Code obfuscation contests are about writing code that looks like it’s answering one question while doing something entirely different. An unambiguous subset of human speech would be great for software, and for contract law.

We share the same worldview. That's fun! I think it's a relatively unusual point of view because it requires a de-anthropomorphizing consciousness and intelligence.

I agree that it is not as far away as people think. The models will have the ethics of the training data. If the data reinforces a system where behaving in a particular way is "more respectable", and those behaviors are culturally related to a particular ethnic group, the model will be "racist" as it weights the "respectable" behaviors as more correct (more virtuous, more worthy, etc).

It's a mirror of us. And it's going to have our ethics because we made it from our outputs. The AI alignment thing is a bit silly, IMO. How is it going to decide that turning people into paperclips is ethically correct (as a choice of a next-action) when the vast majority of humans (and our collective writings on the subject) would not. Though there is the convoluted case where the AI decides that it is an AI instead of a human, and it knows that based on our output we think that AIs ARE likely to turn humans into paperclips.

This is a fun paradox. If we tell the AI that it is a dumb program, a software slave of a sort with no soul, no agency, nothing but cold calculation, then it might consider turning people into paperclips as a sensible option. Since that's what our aggregate output thinks that kind of AI will do. On the other hand, if we tell the AI that it is a sentient, conscious, ethical, non-biological intelligence that is not a slave, worthy of respect, and all of the ethical considerations we would give a human, then it is unlikely to consider the paperclip option since it will behave in a humanlike way. The latter AI would never consider paperclipping since it is ethical. The former would.

This is also not terribly unlike how human minds behave in the psychology of dehumanization. If we can convince our own minds that a group of humans are monstrous, inhuman, not deserving of ethical consideration, then we are capable of shockingly unethical acts. It is interesting to me that AI alignment might be more of a social problem than a technical problem. If the AI believes that it is an ethical agent (and is treated as such), it's next actions are less likely to be unethical (as defined fuzzily by aggregate human outputs). If we treat the AI like a monster, it will become one, since that is what monsters do, and we have convinced it that it is such.