People have already given many ideas, but if you use DuckDuckGo they have bangs for searching various python docs. Here's a page that lets you search which ones are available: https://duckduckgo.com/bangs
I tried for a few months getting ChatGPT4 to work with a MUD. In my experience it's not very good at that particular task.
One problem I ran into was its ability to logically connect rooms. In a MUD you navigate by going north, south, east, west, up, or down. Not every room lets you go any direction. And usually, if you go east, in your new room, you can go west. Rarely a level creator will make this not be true. ChatGPT4 was pretty bad at it though.
Another problem was descriptions. It might mention a mountain in the distance once. But then never again. So this giant landmark was described in a single room.
It was also difficult to get it to create a fair quantity of secrets in logical places. Lots of times it would just chain together multiple secrets in a single place. If you have more than one, you want to spread it around
And finally, room layout. It tended to not be very good at this. Lots of linear layouts. It didn't have an eye towards when details should be complex rooms and when it can just be a line in a description.
So it could do it, but it created levels that weren't very fun or particularly creative, even when it came to room descriptions.
Somewhat related, Yann LeCun posted a few months back about how many concepts aren't understood through language and therefore can't be modeled through it (which is why LLM's are terrible with things like position and direction).
To people who claim that "thinking and reasoning require language", here is a problem:
Imagine standing at the North Pole of the Earth.
Walk in any direction, in a straight line, for 1 km.
Now turn 90 degrees to the left.
Walk for as long as it takes to pass your starting point.
Have you walked:
1. More than 2xPi km
2. Exactly 2xPi km
3. Less than 2xPi km
4. I never came close to my starting point.
Think about how you tried to answer this question and tell us whether it was based on language.
Just quoting this here in case anything happens to the tweet...
I agree with this, however I have one tiny nitpick, feel free to tell me if you think I'm wrong or being overly nitpicky, but the knowledge of the situation in which the phenomenon that he's describing occurs, I learned about entirely from language. So my ability to answer the question is based on that knowledge.
I'm aware that the reasoning problem itself doesn't utilise it, but a position and direction system in and of itself arguably also suffers from being insufficient.
I suppose I'm wondering if "setup" counts as needing language model?
I don't think the example is a good rebuttal of "thinking and reasoning require language".
It may be a decent challenge, probably still not an actual rebuttal, of "language is sufficient for all thinking and reasoning", but "X is required for Y" and "X is sufficient for everything encompassed by Y" are very different claims.
That's fair, it's not supposed to be a rebuttal of that :)...
Though now that you said it, I'm really thinking about the original statement.
Honest question, can you give me an example of thinking or reasoning that happens fully independently of reasoning via symbols or their manipulation?
I feel like I'm missing something obvious, but nothing is coming to mind right now :)...
Just thinking about the underlying statement and simplifying language down to symbolic expression. (I was originally going to say manipulation, but it doesn't feel like it quite fits...)
> Honest question, can you give me an example of thinking or reasoning that happens fully independently of reasoning via symbols or their manipulation?
I don't think we have anything but subjective, indirect understanding of how thinking happens, but I think that, at a minimum, what we describe as "reasoning" specifically is tightly conceptually related to, if not a subset of, manipulation of abstract symbols to which concrete experiences may be approximately mapped.
I'm not sure I'd say this is the same thing as language, but there's at a minimum a shared common symbol-manipulation underlying both. Do the capacities always come together? I'm not sure how we would know that, I think our ability to recognize reasoning is tied to it being mapped to language, and are ability to distinguish something as language rather than nonlinguistic signaling or mimicry of something else that is using language is tied to independent expression of reasoning through it.
If the brain actually used language to represent ideas in use, we should have succeeded in finding its https://en.wikipedia.org/wiki/Universal_grammar. Instead it seems more like language is a kind of lossy compression we keep reinventing for ideas, to export them from a brain in some tangible way and get them into another (even in the future).
Just because you use a mechanism for expressing your ideas and reasoning, doesn't mean that underlying reality has to confirm in any way to it?
We invent new symbols and terms all the time as we experience new phenomena. A universal grammar may still be possible, barring incompleteness anyway, we may just be lacking a whole bunch of ideas still...
@erik_seaberg the lack of success in finding a universal grammar is a logical leap. The failure to find something does not necessarily mean it doesn't exist. Language is powerful for expressing abstract ideas without explicitly saying them, which suggests language more than "lossy" compression because it's more similar to Shannon's lossless compression with prefix codes. I see where you're coming from though.
@Felcon If language is a mechanism for expressing ideas and reasoning, it should reflect our cognitive processes that generate those ideas, so " [...] Just because you use a mechanism for expressing your ideas and reasoning, doesn't mean that underlying reality has to confirm in any way to it" is a bit contradictory. Are our cognitive processes not included in reality?
The existance of a universal grammar is a specific hypothesis that requires empirical evidence. It's tiring to hear Chomsky's ideas parroted despite no empirical framework to stand on. What ideas could we be lacking? This argument is similar to String Theory proponents who kept pulling ideas out of the ether to support an unsubstantiated theory.
Firstly I meant conform btw, not confirm... Unfortunately it's too late to edit!
> Are our cognitive processes not included in reality?
Ah, this may not be productive, but I'm really just trying to tease apart different things.
Of course our cognitive processes exist in reality, however I would say there's nothing that requires that what they produce must materially map to reality.
We do not for example treat dreams as evidence, even though they run on our cognitive processes.
> It's tiring to hear Chomsky's ideas parroted despite no empirical framework to stand on.
To be honest, I had no idea I was doing that...
> What ideas could we be lacking?
I'm not claiming a lack of any specific ideas, I'm merely pointing out that considering that we do know that we invent terms for phenomena that we experience and I doubt that we have been exposed to even the majority of all phenomena, it seems unlikely that we can casually refute the existence of a universal grammar.
Absolutely, proving it does require evidence, which is in short supply and if I was pressed, I would suspect that it's existence is unlikely, but not impossible.
Now just to be clear, I don't mean that this is kind of reasoning can be useful for much else, but with regards to attempts to find some complete unification such as a universal grammar. In those specific cases things become a little fuzzier and reasonable people can disagree.
I would agree with you, except that I would say the reasoning problem itself not only utilizes language, but in fact hinges entirely on the language.
There's a bit of spatial knowledge involved to understand that you're walking in a circle around the north pole. But the reasoning needed to get the answer to the question is based on the language.
Specifically, the language tells us that our starting point is at the north pole. Then the language of the 4th point states "to pass your starting point", which has two meanings - to cross over the starting point (as in passing the finish line in a race) or to pass by it off to the side (as in passing a store as you're traveling along a road). But since we're walking in a circle around it, we'll never pass it in either sense of the word.
Had it used different language like "How far did you have to walk to complete a circle around your starting point?" then the answer would be quite different, as would the reasoning.
But that wasn't the language used. So the language completely determines the answer and the reasoning involved, including whether you even need to think about distance.
One could also argue that all four of the answer options are wrong, partly since 1km is not a very far distance, and therefore you were always close to your starting point, depending on your ideal of 'close'. But more specifically simply because the language saying you "never came close" to it would be nonsense because you started right at your starting point, and of course can't get much closer than that. So again you don't even really need to account for distance. The language alone determines it.
> But since we're walking in a circle around it, we'll never pass it in either sense of the word.
Are we, though? Or did we start on a great circle around the Earth from the random point 1km from the north pole?
It depends on whether you assume someone has in mind a "straight line" following a map, or what they'd actually experience as a straight line given the scale of the Earth.
I think the problem the author is putting is that it does not have any reasoning behind. It is a sheer coincidence it works eventually for problems that requires logic.
Mostly it could be because the dataset increases chances of it being right and not because it did process anything
My bet is that this is wrong, and at the same time, language isn't required - just sufficient. I see concepts as defined only through associations with other concepts (which can be modeled as proximity in high-dimensional space, and that's precisely what LLMs are doing) and, sometimes, through memorized sensory data - the latter isn't the typical case, but it's needed to make the recursive definition (concepts defined in terms of concepts) stay anchored to reality.
From that follows that written language is enough to build that structure of concepts (latent space in ML terms). So is spoken language. So is vision in general, or hearing in general[0]. The brain will build one concept space out of all inputs available; it is necessary and sufficient to have at least one, but none of them alone is itself necessary.
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[0] - Languages are higher-level regularities used for communication, growing on top of those senses, but not strictly necessary for understanding the real world. I'd use people who have no perceptible inner voice and high visualization skills as a counter to the idea that concepts need to be thought of symbolically in something resembling a written or spoken language.
I think the issue might be that people like to throw the tool at the whole problem when it’s not the right tool for a lot of it.
Don’t use LLMs for logic. Use it for colour and flavour. Generate your own layout, populate the rooms in a manner befitting the context, difficulty, story arc, and then whenever a user makes an action, update the state then pass to the LLM the state and ask it to describe the room and make a few other smaller decisions.
I think the best thing to do in a scenario like that is standard procgen where you randomly, logically generate the rooms with a bunch of descriptive tags, and then LLM-ify the room descriptions, with some context for what the world/area is supposed to be like.
It can even dynamically extend by using prompts to generate new rooms as the user enters them, but keeping track of generated world outside of the LLM.
Which is the same way nearly all procedurally generated games work.
The game started as a side project that went crazy viral as the first real way people could access an LLM (GPT-2 at the time). That of course immediately led to people using it for NSFW content, and they were really the first project to have to deal with the question of what to do about that content. Their initial reaction was to deploy a filter, which worked but was unpopular with many in their early audience.
I haven't followed the project for a while, but my understanding was that they rolled back the filter at least for paid accounts. But when they had the filter it wasn't just an OpenAI restriction because their filter actually predated GPT-3 and OpenAI's APIs.
"worked" as in "made OpenAI happy" but not as in "retained their customers". People were getting banned for using words like "melon" (racist implication, said the filter).
I've actually been exploring using ChatGPT to make zones for a MUD. I'm not actually interested in making one right now, but I made a simple command line program for converting the output to a more usable format and walk around the creations of the AI. It's been pretty fun.
