GPT-4 Designed a Programming Language

>It doesn't understand anything. It combines symbols according to a probabilistic algorithm and you assign meaning to it.

This is what the human brain does. I'm not assigning meaning to it. I am simply saying the algorithm is isomorphic to our definition of the word "understanding". No additional meaning.

>Because you keep replying with statements indicating you are yet to grasp it.

No no. What's going on here is I'm replying with statements to help YOU understand and you are repeatedly failing.

>There is just as much evidence for sentience as understanding.

Sentience is too fuzzy of a word to discuss. We can't even fully define it. Understanding is less fuzzy and more definable thus the question and claim for "understanding" is a much more practical query.

A human can be inconsistent and even lie. It does not mean the human does not understand you. Thus because your logic is applicable to humans it is akin to saying humans don't understand you. That is why your logic is incorrect.

There is no "desire" in the computer. Therefore the question of whether its desire is different from our desires is meaningless, because it does not have a desire.

Computer just executes instructions. It doesn't matter to it whether its desires are fulfilled or not. Whereas humans do have desires: If we get thirsty we suffer unless we get our desire of drinking fulfilled.

> This is not surprising. A human would suffer from similar errors at a similar rate if it were exclusively fed an interpretation of reality that only consisted of text from the internet.

I think this is surprising at least if the bot actually understands, especially for domains like math. It makes errors (like in adding large numbers) that shouldn't occur if it wasn't smearing together internet data. We would expect there to be many homework examples on the internet of adding relatively small numbers but less of large numbers. A large portion of what makes math interesting is that many of the structures we are interested in exist in large examples and in small examples (though not always) so if you understand the structure, it should be able to guide you pretty far. Presumably most humans (assuming they understand natural language) can read a description of addition then (with some trial and error) get it right for small cases. Then when presented with a large case would generalize easily. I don't usually guess out the output and instead internally try to generate and algorithm I follow.

> Take for example: https://www.engraved.blog/building-a-virtual-machine-inside/

When I first saw that a while back, I thought that was a more impressive example but only marginally more so than the natural language examples. Like how these models are trained under supervised learning imply that it should be able to capture relationships between text well. Like you said, there's a lot of content associating the output of a terminal with the input.

Maybe this is where I think we're miscommunicating right. I don't think even for natural language it's purely just copying text from the internet. It is capturing correlations and I would argue that simply capturing correlations doesn't imply an understanding. To some extent, it knows what the output of curl is supposed to look like and can use attention to figure out the website to then generate what an intended website is supposed to look like. Maybe the sequential nature of the commands is kind of impressive but I would argue that at least for the jokes.txt example, that particular sequence is at least probably very analogous to some tutorial on the internet. It's difficult to find since I would want to limit myself before 2021.

It can correlate the output of a shell to the input, and to some extent, the relationships between the output of a command and input are well produced and its training and suffused it with information about what terminal outputs (is this what you are referring to when you say it has to derive understanding from internet text?), but it doesn't seem to be reasoning about the terminal despite probably being trained on a lot of documentation about these commands.

Like we can imagine that this relationship is also not too difficult to capture. A lot of internet websites will have something like

| command |

some random text

| result |

where the bit in the middle varies but the result remains more consistent. So you should be able to treat that command result pair as a sort of sublanguage.

Like as a preliminary consistency check that I just performed right, I basically ran the same prompt and then did a couple of checks that maybe show confusing behavior if it's not just smearing popular text.

I asked it for a fresh Linux installation then checked that golang wasn't installed (it wasn't). However, when I ran find / -name go, it found a Go directory (/usr/local/go) but when I run "cd /usr/local/go" also tells me I can't cd into the directory since no such file exists which would be confusing behavior if it wasn't just capturing correlations and actually understanding what find does.

I "ls ." the current directory (for some reason I was in a directory with a single "go" directory now despite never having cd'ed to /usr/local) but then ran "stat Documents/" and it didn't tell me the directory didn't exist which is also confusing if it wasn't just generating similar output to the internet.

I asked it to "curl -Z http://google.com" (-Z is not a valid option) and it told me http is not a valid protocol for libcurl. Funnily enough, running "curl http://google.com" does in fact let me fetch the webpage.

I'm a bit suspicious that the commands that the author ran are actually pretty popular so it can sort of fuzz out what the "proper" response is. I would argue that the output appears mostly to be a fuzzed version of what is popular output on the internet.

Not the person who you posed the question to, but I believe their point may be that Go is a fully described game, a constrained 'space' even if that space is remarkably deep.

Our world is not a fully described game (unless you want to take a radical philosophical position, and in which case we still don't know the rules of this game). We talk about and think about this world in language. Training a machine on human language and then after training, having that machine take language inputs and generate language outputs is not the same as training a machine to 'play' Go because the two worlds they have been trained in (1. the game of Go; 2. the real world) are fundamentally not equivalent.

That quote reveals either that they are 1) delusional or 2) a fraudster. Your comment leans more towards 2) but I think 1) is also a possibility, which in some ways I find more concerning (delusional cult leaders being potentially more dangerous than common fraudsters).