And all of our surprising wins and awful mistakes had explainable reasons, dammit; it wasn’t just a misfiring of trained statistical networks!
It is only if we narrow thought to mean precisely human-like thought when humans and human creations are uniquely capable of something. To that extent, our models of intelligence is very much in the pre-copernican era.
Slime molds and amebas might be able to reason abstractly to some degree but they can't write code or poetry.
How do you know fungal networks don’t write and read poetry under the forest floor? If they do—and we have no reason to doubt that they do—you wouldn’t be able to read them, let alone understand them.
The earth’s biosphere as a whole also writes code, just in DNA as opposed to on silicon transistors, why exclude the earth’s biosphere from things capable of abstract thought?
yes, that is the sense in which we are discussing intelligence in order to debate whether the human brain and LLMs operate on similar phenomena
This would be like finding a flower which produces a unique fragrance, then create a perfume which approaches the same fragrance and then conclude that since these are the only two things in the universe which can create this fragrance there must be something special about that perfume.
> is an uninteresting fact if we define “abstract reasoning” to be exactly what humans do, and then create models with the goal of recreating exactly that
if you find this uninteresting, we have perhaps an irreconcilably differing view of things
I’m not saying these language models—or my hypothetical perfume—aren’t an amazing feat of technology, however neither has any deep philosophical implications about shared properties other than the ones constructed to do so. Meaning, even if LLMs and humans are the only two things in the universe that can reason abstractly in the same way humans do, that doesn’t mean the latter has any more properties shared with the former.
For an example, crows can effectively use tools and communicate abstract concepts to one another from a memory. Which means they can observe a situation, draw conclusions, and use those conclusions to act as well as make decisions on how to act. That would seem to meet the bar for reasoning abstractly.
Of course… The hole in that theory is that evolution never found the wheel.
The steel man in that theory is that it invented the neurological and social processes that then went on to invent the wheel. And the platypus and the clap.
Edit: I forgot to bring it back around and make a point ;)
I’m saying that humans invented clocks and CPUs. We only have metaphors that have emerged from the still misunderstood ether of the informatic universe.
That’s still the hole in my theory of consciousness. I admit it ;)
But it doesn’t give me as much cognitive dissonance as others to believe that the process of performing moral actions still has to be “processed” by me, a processor. In some sense.
The LLM value add for coding is less than the value add of syntax highlighting in my experience.
In my experience and it's certainly useful for unit tests speeding things up for me pretty dramatically.
Also when working on a new development language was quick to point out "how you do that" with the inline vars I needed manipulated vs look ups in Google and copy pasting.
To solve ourselves is to know ourselves completely, and to know ourselves completely is to be honest in who and why we are what we are simultaneously across all persons. It assumes perfect knowledge.
There is no statistical approximation nor computational power which can do this.
> People are understandably desperate to understand their experiences as more than an encoding of a thing that might be explained.
Another way to frame this is, "some people are nihilists and do not see life as more than an encoding of a thing that might be explained."
To know anything (an X) completely you need perfect knowledge. Hence people come up with a set of simplified ways of reasoning about X. They call this a model of X.
Model is incomplete and so primitive, so dumbed down, that we manage to play it forward/backward in our heads or our computers.
If a model checks out with the real outcomes we proudly exclaim that we understand X.
I'm not being sarcastic, that is just a real method we use all the time.
Agreed.
> Hence people come up with a set of simplified ways of reasoning about X. They call this a model of X.
A "set of simplified ways of reasoning about X" in order to create a "model of X" does not imply complete understanding. Quite the contrary actually.
To wit, science often models current understanding of a phenomenon. When new evidence (understanding) is discovered, the model is updated to account for it. Sometimes this invalidates the original model, often the model is refined. Either way, progress is made with the tacit agreement that the model may change in the future.
> If a model checks out with the real outcomes we proudly exclaim that we understand X.
Again, this does not support the assertion of "That's been solved long ago." If anything, it affirms there is justification for disagreeing with the original premise to which I responded:
> We just can’t accept that we might solve ourselves.