ChatGPT generated a puzzle game
puzzledpenguin.substack.com
puzzledpenguin.substack.com
Seems to be similar to a game called Kakuro. This [1] repo even contains a similar rule:
> The algorithm exceed the rules that the sum over a row must equal to the value on the left and the sum over a column must be equal to the value on the bottom of the cells with the diagonal and one or two numbers
Ride those coattails and take other peoples ideas as your own!
But it is not synthesizing an understanding of the game of chess.
> And to the best of you knowledge this type of puzzle does not currently exist?
and it responded:
> As far as I am aware, this specific type of puzzle with the given rules and mechanics does not currently exist in the puzzle game genre. However, there may be similar games out there that share some similarities with this puzzle.
That response is not generated (as far as I am aware) by any form of logical analysis or understanding, it's just generated text based on its training and prompting. It was asked to come up with something "new", and will continue to claim that as it was part of its prompts.
So yes, this may not be a failing of ChatGPT, but of users understanding of it. You cannot take what it states as "fact" as anything other than potential BS. But it is an incredible tool for using to generate text and code.
We are still early in its development though, who knows where it will be in 18 months time!
Looking at the response the way you suggest, it's clear it's given a boilerplate answer that would seem likely given the context it has found itself in.
If words not right said for listen like now, think you might not be smart as is tho.
And as for whether ChatGPT has an agenda or not, that is beside the point. People can and do use it as a tool for plagiarism while trying to hide behind a layer of plausible deniability provided by the "black box" of the model. This cannot be allowed to continue. This is why we need to push back, just as the GP is doing.
> People can and do use it as a tool for plagiarism while trying to hide behind a layer of plausible deniability provided by the "black box" of the model. This cannot be allowed to continue. This is why we need to push back, just as the GP is doing.
This is absolutely preposterous. People are going to lie and plagiarize whether they have a chat bot do it for them or not. The existence of a chat bot isn’t going to be the make or break in this equation and if anything, the people using it for that purpose should be rightfully vilified rather than the tool.
The consequences actually are quite serious. A person falsifies work product once in an academic or professional setting and their career is severely impacted. This is why people are "surprised" to encounter such a BS generator operating under the trademark of a reputable company.
It’s almost as if you ignored everything I said, cherry-picked a random part, then went on a tangent about a different part of my comment. All without actually comprehending what the things you replied to said.
The difference is, with a chatbot it might not even be a conscious act, the chatbot is doing it for you and you're not aware that it's happening.
I've had it generate search terms that could be used to verify "facts" in is answer. Then I'd give it the page results and have it adjust and source it's answer using that.
Have not tried it yet, but perhaps Bing's implementation is a step in that direction?
More dangerous than ChatGPT is the sheer gullibility of many people putting it to use.
This obviously isn't the intention of the software, it's just an LLM after all, but there's something missing in the experience when it comes to working with code. Hopefully this sort of issue can be corrected.
Intuitively it makes sense to me that broken code would often be very close to questions about how to achieve something in code.
Some want to talk of these LLMs as approximating an intelligent actor. If that's the case, then we also need to assign metaphors for things like deceit and coercion. We also need to consider assignments of novelty to what's generated and think of their rights as quasi-sentient, etc.
Some want to talk about them as probabilistic text token generators, which brings the benefit of not being intelligent or independent actors at all really but also then comes with the issue of intellectual property theft in training them on information not licenced for reproduction or commercial use.
The industry prefers to thread the needle between these as the former case brings some pretty wild conversations and the latter may mean lawsuits.
Is it? Even if it’s fair to assume that now, we have no idea if that will remain true or when the shift will happen.
The CEO of OpenAI is the same scammer who scanned eyeballs in return for a non-existing cryptocurrency[1] and the company itself is criticised all the time[2].
[1]: https://www.buzzfeednews.com/article/richardnieva/worldcoin-...
[2]: https://techcrunch.com/2023/03/01/addressing-criticism-opena...
There is no reason to assume “the CEO himself” would personally do it. History is full of bad CEOs making harmful decisions and they definitely don’t need to (and often wouldn’t even be able to) do it on their own. Sam (presumably) isn’t out there personally scamming more people for their retina scans, but someone is: https://news.ycombinator.com/item?id=34981352
For instance, I once found what I thought was an ingeniously original idea about about how TV is really just a kind of reflection of reality akin to Plato's Cave. I immediately got started writing a thesis about it, but I didn't have to search for long on the topic before I found an entire book written on this way of thinking about television. I wasn't really disappointed, because in the back of my head I knew that it had too be too good to be true that I'd be first with such a great idea. In any case I kept working with the thesis, and I still did got a good grade on it despite the idea not being revolutionary.
The questions I now wonder about is, can ChatGPT forget? Or could it be that ChatGPT was never exposed to this game, but could still infer it through other game rules, such as those for Soduko? Which I guess opens up another rabbit hole on if or how AI can be creative. Which I guess opens up another rabbit hole on how creativity works in general.
There is no way, the game type is centuries old, you can read this giant wikipedia articles about games like this.
https://en.wikipedia.org/wiki/Magic_square
ChatGPT "inventing" this is like thinking it invented chess.
Point about magic square is that every culture invents games like that, it is one of the most basic puzzle ideas humans have, I don't see how ChatGPT can't have that in its training set.
All that you’ve done is shown that similar types of puzzles exist. Which, I mean, is kind of the point of a generative AI.
“Games like this” exist. Does this specific game exist?
It’s not enough to say “a lot of games with similar rules exist” and if anything, that just shows that a generative AI is good at what it does: break down the rules of a game and make modifications to make what is potentially a new game.
If you can show an example of this exact game having existed for centuries, then you have a point. But showing that magic squares and similar games exist… just shows that magic squares and similar games exist, not that the algorithm incorrectly said this is a new game.
> It’s not enough to say “a lot of games with similar rules exist” and if anything, that just shows that a generative AI is good at what it does: break down the rules of a game and make modifications to make what is potentially a new game.
No it doesn't, even if that is the case it just shows that it adds random variations. Since we only see the trimmed subset of ideas it generates that people found good enough to post, the smart one is the person.
You would need to prove that ChatGPT actually consistently generates working puzzle ideas that are novel to convince anyone that it actually does so. Extraordinary claims require extraordinary evidence, so all I need to do is find plausible explanations to how ChatGPT found it, you would need much better evidence to convince people it actually did make a novel game.
If this were the case, it would have been trivial for you to find a game with its written rules described and which match the one generated.
You have done nothing but say that is the case. You haven’t actually proven that’s the case.
ChatGPT can’t magically infer the rules of the game from screenshots, and you have only shown that similar games exist and have existed for centuries. But that is not the same as saying that this specific game has and that ChatGPT just pulled it out of its dataset.
That is the extraordinary claim that you don’t have evidence for but are acting like it’s right there obviously out in the open for everyone to see.
Search engines doesn't work like that. You are basically asking me the equivalent of proving that a photo isn't depicting a ghost. No, I can't prove that, I can however come up with examples showing how the photo could have been created even if it wasn't a ghost.
If you want to prove that ghosts are real you need plenty of photos from lots of angles and situations, or videos, and from many sources to show that it isn't all made up by a single person. The equivalent of that would be if they had made ChatGPT generate 100 different working games for example, that would be much more believable. But a single case of a game that already exists and has countless texts describing similar games? It just looks like random chance that got handpicked or plagiarism.
This isn't a court trial, I am not going to sue ChatGPT for plagiarism here, it is just a discussion whether it is reasonable to believe ChatGPT can generate novel puzzle games.
Edit: But do note that since ChatGPT can find such ideas that are hard to find with a search engine, that makes ChatGPT very useful in a way search engines aren't. So I am not saying it doesn't add value. Just that people seem to say ChatGPT does a lot of thing that it doesn't seem to be able to do.
Edit again:
> That is the extraordinary claim that you don’t have evidence for but are acting like it’s right there obviously out in the open for everyone to see.
Yes, you think it is obvious that ChatGPT is capable of very creative and productive thinking. But most people don't think that, to them that is an extraordinary claim. I'm not here to convince you, I'm here to explain to you why you aren't convincing anyone with what you say. People like you were convinced by articles like this before the discussion even began.
The claim was that it pulled the game out of its dataset. If this were the case, I would argue it would absolutely be trivial to find them. It’s not some concept that can’t be described in words or would be hard to quantify. The rules have been provided, and, assuming they were plagiarized from somewhere else, would be listed verbatim or close to it.
If a student plagiarized on their work, whether in written form or in code, it’s been trivially easy to find the exact work that was copied from. It generally takes me a few seconds of searching to find it.
This is the same. If these rules existed in a dataset, then it should be equally easy to pull them up and prove the plagiarism. If all you can find is similar puzzles, you can’t just throw your hands up and say “yep, gottem”. That’s just not how this works.
ChatGPT uses word vectors, it wont use the same words but variants of the words. You can't search for that. Cases where word vectors only maps to single words with no variations for every word are very rare, so ChatGPT is very good at plagiarising things without reproducing exactly, it just rarely fails at it.
> If a student plagiarized on their work, whether in written form or in code, it’s been trivially easy to find the exact work that was copied from. It generally takes me a few seconds of searching to find it.
No it isn't, they just change the words and rewrites it until it no longer looks the same. ChatGPT is trained to rewrite texts like that to avoid triggering trivial plagiarism detectors. They train it to produce the same text, but with different words, producing exactly the same text is punished.
Do you think students plagiarizing don’t do the exact same thing? Clearly someone has never actually dealt with plagiarized work. This is plagiarizing 101. The structure remains the same even if they use synonyms. Considering it’s trivially easy to find in code which is magnitudes harder to pull off, I would still argue it should be easy as pie to find this supposed set of rules.
Your point is not very credible without proof of this game existing and ChatGPT pulling it from this source. Without showing this supposed proto-game having existed with rules the ChatGPT can pull from, then all you’ve done is wave your hands around and yelled “similar games exist so this can’t possibly be uniquely generated” and that’s not a very compelling argument.
You rewrite the structure of the text, you don't just use synonyms. ChatGPT is capable of rewriting text to a different structure while keeping the meaning, I hope you are aware of that.
Anyway, even if you just change the words to synonyms it wont be easy to find in a search engine. Search engines aren't very good at finding matches to synonyms. Google tries, but in doing so they fail to find more specific texts like scientific publications or documentation, so no search engines aren't good at finding plagiarism.
Edit: And you make it sound like most plagiarism is found. No, that isn't the case, most plagiarism is not found out because it is a very hard problem to solve. Only the most blatant cases are caught. For humans that is reasonable, for AI we can be stricter since there isn't a humans career at stake.
Got it, so you’ve never actually dealt with plagiarized work. You should have just led with that.
I have literally said, from actual experience, that this is the case. But I guess discarding that and pretending it was never said and that the opposite is true is I’m sure an easier position to hold.
For students they are probably easier to catch since they use the same tools you do, they use a search engine to find an article and plagiarises that. But ChatGPT takes deep discussions from reddit or stack overflow, I can't find those with a search engine.
Yet here we are. Dozen comments later and still no written set of rules produced which definitively shows that it was copied.
Come back when you actually have that and maybe we can continue this conversation.
> But ChatGPT takes deep discussions from reddit or stack overflow, I can't find those with a search engine.
Where do you think the answers come from? It’s not like Google has a massive index island around Reddit and SO.
So maybe these rules are described in Japanese? Most similar games comes from Japan, Kakuro, Sudoku etc. Would your plagiarism detection method of Googling it find a Japanese source? I doubt it. But ChatGPT transcends language barriers, it can translate to English just fine.
[0] https://steamuserimages-a.akamaihd.net/ugc/18583143573725211...
this comment thread started with this link, this is exactly the same game
ChatGPT can't deduce the rules of the game using the screenshots. They would need to be written somewhere for them to come out of its dataset. And so far, nobody has shown a game with the rules in a format that ChatGPT could consume.
Why is it so hard to believe that a generative AI generated this game from similar ones which exist? That is literally the purpose of it, after all.
there's a quite long article from Stephen Wolfram about how it works and this is why I belive it can't do that: https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-...
However it generates a text, that text may describe what for practical purposes is a new invention.
And how do we think exactly? Don't we have a brain trained on input (livable experience, knowledge from books, school, videos, conversations, etc) and generating text based on probabilities (weighted sets of neurons with weights built from that set)?
If I told you “We need a brand new, never-never-before-seen puzzle for our next game release.” and you searched Google for “brand new, never-before-seen puzzle”, found a puzzle game with those words in its marketing copy and pitched it to me, that would be some combination of unintelligent and dishonest behavior. Like, surprisingly so. It’s different from forgetting some puzzle you played with as a little kid and thinking you made it up, or creating a puzzle you’d never seen but has been made before.
We train it to predict the next word based on the training data, that is true. But we still have no idea what kind of internal structures said training actually produces inside of neural net. It sure as hell isn't just a "stochastic parrot", though, which is rather obvious if you ever tried giving it a complicated multi-step task and solve it while "thinking out loud".
I was answering the question “But how is this different from a person?”. Being asked for something new and finding something that already exists with the word “new” in front of it isn’t normal human behavior. That’s how it’s different from a person.
Zooming out a bit, I think there’s some confusion in this whole chain. There’s a common topic about ChatGPT you could call Question of Creativity. If you ask for a new poem, it just smashes together its patterns around poems. You can debate if this is creativity, and if not, how are humans different. A few comments up, someone brought in a different idea you could call New Matching. If you ask for a new poem it will just grab you a poem that had the words “new poem” in front of it. New Matching is a different idea than Question of Creativity. The person I replied to seemed to be mistaking one idea for the other.
I don't know what introspective is, but I know it when I see it. People around me genuinely come up with new concepts---some of what they came up decades ago with is now ubiquitous---and the sources is often not language. It comes from observing the world with your eyes, from physical or natural mechanisms. If you want to put it into the language of models: we just have so much more data to draw on. And we have a good feedback mechanism. If you invent a toy, you can build it and test it. Language models only get second hand feedback from users. They cannot prototype stuff if the data isn't out there already.
Wouldn't your "something from scratch" idea, be based on your "training set" (knowledge you've learned in your life), and ways of re-arranging it inside your brain, using neuron stuctures created, shaped, and reiforced in certain ways by exposure to said training set and various kinds of re-inforcement?
Still a training set though. There's no some magic non-training part creating stuff from zero, out of pure determination!
In principle, ChatGPT cannot forget. It is trained on data and this training will stay as long as it didn't get deleted or destroyed. In other words, in all cases of someone having made ChatGPT tell something, it should be possible to repeat this. Perhaps in some case it will be effectively impossible for some rare combination of prompt and random seed, so one could say, ChatGPT forgot something. But this is not the same as people forgetting something.
Or during the training something was not considered important, but this is not forgetting, this is ignoring.
Ironically, it seems to me that you are anthropomorphizing ChatGPT a bit too much here. It has no reason to lie so I think it's more likely that it just doesn't know such game exists. It probably came up with it independently or doesn't have a strong memory of it. In some respect, it would be even more impressive if it was actually "lying through its teeth" because it would imply the AI had some kind of hidden agenda.
I'm not sure I'm comfortable with "remembers" either. My gut says I want to say I'd be more comfortable with that word for a web cache, but due to my understanding of human memory as constructive maybe I should be more comfortable with that for an LLM than for any other software.
Happy to be convinced otherwise.
However, it will fail immediately when you ask it to print an ASCII chart of Harry Potter's family tree, because it does not actually "know" anything, and it will make all sorts of odd connections.
The clearest observation I can make of ChatGPT's success is that the general public is quite ill-informed and easily impressed by theatrics, both lessons we've already learned from politics.
To demonstrate this a bit, I asked for HP's family tree as JSON, suitable for use in a charting library, and this is what it came up with:
---
{ "nodes": [ { "id": "Harry Potter" }, { "id": "Ginny Weasley" }, { "id": "James Potter" }, { "id": "Lily Potter (née Evans)" }, { "id": "Arthur Weasley" }, { "id": "Molly Weasley (née Prewett)" }, { "id": "Fleamont Potter" }, { "id": "Euphemia Potter" }, { "id": "Mr. Evans" }, { "id": "Mrs. Evans" }, { "id": "Vernon Dursley" }, { "id": "Petunia Dursley (née Evans)" }, { "id": "Dudley Dursley" }, { "id": "James Sirius Potter" }, { "id": "Albus Severus Potter" }, { "id": "Lily Luna Potter" } ], "links": [ { "source": "Harry Potter", "target": "James Potter" }, { "source": "Harry Potter", "target": "Lily Potter (née Evans)" }, { "source": "Ginny Weasley", "target": "Arthur Weasley" }, { "source": "Ginny Weasley", "target": "Molly Weasley (née Prewett)" }, { "source": "James Potter", "target": "Fleamont Potter" }, { "source": "James Potter", "target": "Euphemia Potter" }, { "source": "Lily Potter (née Evans)", "target": "Mr. Evans" }, { "source": "Lily Potter (née Evans)", "target": "Mrs. Evans" }, { "source": "Petunia Dursley (née Evans)", "target": "Mr. Evans" }, { "source": "Petunia Dursley (née Evans)", "target": "Mrs. Evans" }, { "source": "Vernon Dursley", "target": "Petunia Dursley (née Evans)" }, { "source": "Dudley Dursley", "target": "Vernon Dursley" }, { "source": "Dudley Dursley", "target": "Petunia Dursley (née Evans)" }, { "source": "James Sirius Potter", "target": "Harry Potter" }, { "source": "James Sirius Potter", "target": "Ginny Weasley" }, { "source": "Albus Severus Potter", "target": "Harry Potter" }, { "source": "Albus Severus Potter", "target": "Ginny Weasley" }, { "source": "Lily Luna Potter", "target": "Harry Potter" }, { "source": "Lily Luna Potter", "target": "Ginny Weasley" } ] }
---
Sorry about HN formatting, but you get the idea. This looks fairly accurate to me. What about this demonstrates less "reasoning" then turning it into an ASCII chart?
Anecdotal, but I've not yet had any success in producing any non-trivial code with ChatGPT. It has, however, produced copious amounts of bullshit with plausible variable names... :)
It's pretty good in JS, it sucks in Rust
That game is NOT the same game. It's similar but the games are different.
Loose quote from I don't remember who, early 90s.
"Rule 34: If you can imagine it, it exists as Internet porn."
I get people are excited about a chatbot which doesn’t suck, but ideally it wouldn’t turn off critical thinking skills.
[1] https://trends.google.com/trends/explore?q=Sumplete (search "Worldwide" and extend the time range)
[1]: https://www.linguee.com/english-spanish/search?query=sumplet...
[2]: https://www.linguee.com/english-spanish/search?query=suplent...
Your game involves addition. chatGPT is using subtraction.
Would be nice if GPT could dump the source of how it came to such a solution, if it generated the game by random chance via combining various unrelated chunks of text and mixing up the rules, or if it used some text describing the game you linked.
I think this is an interesting note at the end, it's clear that the whole "conversation" hasn't been posted, and not clear how many prompts were needed to finish it. A proficient developer would be able to develop this same app to the same level (once they have the idea) in a couple of hours without ChatGPT too.
It would be super interesting to see a full screen recording of the process (or a similar one). What was the total word count of all prompts, how does that compare to the code size?
Don't get me wrong, this is incredible and inspiring (I'm regularly using ChatGPT and Copilot). But I think the post doesn't critically analyse the process well enough.
It was quite amazing how much actual manual work was going into some (not all) of those images in the end.
A lot of processing in photoshop etc. I actually started to think that really, he was doing art, just not using a brush.
Artists will use ML as engineers have been using ML such as in https://youtu.be/aR5N2Jl8k14?t=198.
I can understand the clash with artists not wanting their work absorbed by the machine, and I agree to a point: if the model reproduces their art 1:1 (or close to) then that's bad! For the artist and the model! If it simply takes inspiration for the type of art/style etc from other artists' work, well, that's what artists do themselves already! That's literally how people learn to be artists.
But also, for an artist to complain that it's not really artistic, then where do we draw the line? They'll use a brush in photoshop that they don't have total control over the behaviour of and that's apparently fine.
I mean... the whole point is that you don't need to be that proficient to use ChatGPT.
If ChatGPT is much better than a proficient developer, you and I wouldn't be surfing HN, but on the street protesting for universal income.
Would it be noteworthy if it this game (whether or not it existed before) were designed and implemented by someone who has very limited experience with software development in a few hours? Well, the fact that ChatGPT did this means the former is now a very real possibility.
That you can go from conceptual inception of a framework to a fairly complete product in a few hours with very little experience is a big deal.
Because the game has existed for centuries. ChatGPT claiming ownership is nothing new, either. The current top post even links an android app that does the same.
i) This exact puzzle predates the app ii) A description of the rules appears in the training set
Lichess and chess.com both exist. does the existence of one make the other worthless? unimpressive?
That it also coded it up itself is pretty amazing, but it's overshadowed by the false more amazing claim that it invented it.
I haven't tried to replicate the author's journey, but in my experience it requires a considerable amount of hand-holding. e.g. Functions will be stubbed out, but contain no logic.
I was able to guide it through a "playable" flappy bird, bit it took several revisions where I pointed out what was wrong/needed to be done before it truly returned a functional error-free prototype.
It felt like pair-programming with a promising and apologetic junior dev.
The "Labyrinth Sudoku" description feels like a classic language model speciousness. It doesn't actually work: you can't fit the digits 1-9 if you can't use all the cells, and it hasn't modified sudoku rules in a way that makes paths relevant. Maybe you can come up with a way to salvage it, but ChatGPT didn't.
The initial rules for Sum Delete should be read with this in mind: it sounds reasonable, but there's no reason to trust that it can make a puzzle at all, let alone a good one. Also, unsurprisingly, the provided puzzle isn't solvable (the 25 column requires use of the 9 in the first row).
Similarly, I'd love a critical analysis of the initial code. Did it guarantee solvability? An awful lot can be swept under "improving the design".
- Bah, it's not very fun.
- It's been done before.
- It took too long to make.
Seriously. Let me repeat that. An AI generates a game. It comes up with the rules for the game. It even writes the code and designs the web page for it!
Come on! This is amazing!
For such an obscure game I would guess it came up with the rules. It’s difficult to prove though.
I've noticed the same thing testing it on various coding questions. It's extremely good at problems that have solutions online. And given stackoverflow, that's a lot of problems. If you manage to hit it with something that it hasn't seen before though, even if it's conceptually very straightforward, it tends to just generate a mix of boilerplate and nonsense.
As long as the task is in it's training set, it can give you a decent answer, but it can't code it just mimics doing so...
It's perfect for what is a python function for doing X. But it's honestly 50/50 whether that function even exists.
But is it? 99.999% of software development has been done before. Even if you do something that is legitimately new (like creating a chatbot that can generate code on demand). Then your solution will still contain more than 99% code that is just a repeat of things that have already been done.
To be asked in plain, simple (ish) English to invent a game, produce code for it and then style it etc and the few other bits the author asked for _is_ impressive.
Why are we asking for so much? Remember the chatbots of the mid-2000s? Eliza etc? They were impressive for the time but GPT represents a _huge_ improvement in this stuff. Of course it's not perfect, but it's an exhilarating jump in capabilities.
That defeats the point of your argument that “AI generates a game. It comes up with rules for the game”.
No, it doesn’t. It plagiraised the game and pretended to come up with it. It just used a random puzzle game that it had on its training set.
It’s like asking it to write a poem and getting the same exact poem from a random google search. It didn’t come up with it. It just copied it. It’s not as amazing as you say it is.
Also if you look I comments you can see that it’s not even just one game. There are several games that are exactly like that. Which means more probability of having it in a training set.
No, it's not. A better comparison would be a poem that feels the same as an existing one and using the same prose but with its own words. Or any musical plagiarism dispute where the song is clearly different but similar enough that it needs to be decided by court. ChatGPT is not just copypasting a puzzle game here.
Only a small percentage of our output is unique/original, otherwise we live to produce very similar output to what we've had as input.
Common phrases, hell all languages are examples of this. Mimicry of behaviours; it's literally the learning process that evolution gave us that puts us (and other animals) above much simpler creatures.
GPT isn't perfect, but it's like a dog observing that you fetch the newspaper every morning and then it starts fetching it itself for you, then the neighbour is like "well, it's not _originaaal_".
Correct me if I'm wrong, but ChatGPT is a very fancy auto-complete function. It's has no ability to create from scratch, just the ability to recompile and recontextualise any of the many existing pieces it has in its library.
It's unlikey that this game or its rules are truely original, ChatGPT will have just plucked it from the library, perhaps given it a new name.
"Great artists steal".
Art is defined by remixing the life experience of the author.
ChatGPT's ability to create art is only limited by it's input (text corpus) while humans have images, sound, smell, touch, etc.
The GPT version of me can only remix the world I am already in, so this version mostly paints dark landscapes and violent imagery, however much I prompt myself to draw something pretty, it always comes out looking a little macabre.
The regular old person me, on the other side, is plagued by the human afflictions of desire and fantasy. This version of me can only paint the beach on my postcard, but because of my desperation, focus, and need, these paintings become larger and more fantastical than I thought I could imagine, but in that, they provide me and my loved ones comfort and escape and novelty.
The human version of me makes statistically improbable things, but, to me, is still a plausible human, and the one I'd rather be at least.
All just to say, maybe there is a more qualitative difference here than you think.
A human imagining orcs and one horned horses has 'fantastical, larger than life' imagination but AI generation drawing people with strange hands is 'incorrect'.
These are not one to one examples but the point stands that with enough suspension of belief, people are more likely to take on human creations at face value than AI when they know the source.
This suggests a qualitative difference between the two when it comes to "creating" or "generating" that feels far from trivial, even if you want to say the AI can make "good" things, whatever that means to you.
The scope of the creation and whether it actually produced something novel is quite important to the discussion and part of the claim (although the author is very open to be proven wrong, in the article).
Your claim n the second to last paragraph is false. That's relevant. This is HN.
I worry that a lot of otherwise brilliant developers are going to get blindsided by this stuff.
The current models are impressive in strong, quantifiable ways. They are only going to become more powerful from this point.
Consider the current state of affairs: ChatGPT supports a 4K context size. Leaked foundry pricing indicates models that can handle 32K context size. 32K tokens is enough for your entire brand manual or several days worth of call center transcripts. Many products could have the most important parts of their codebase completely loaded into just the prompt.
I would say you should at least try the OpenAI playground (or equivalent technology) to understand what is possible right now. I had no clue where we were at until ~3 weeks ago. I wouldn't wait until 2024 on this one anymore.
But it hasn't! This is just another step in the BS storm coming out of the latest AI hype. The language model has reproduced something that has existed before and was likely part of its training data. That's cool, but it's far from what's being claimed here.
We really need to get better at fact checking this stuff. And with "this stuff" I mean the output of LLMs and other AI frameworks as well as the claims about it. And with "we" I mean society as a whole and our industry in particular. Let's keep the hype in the drawer. The general population can be hyped up about sth, but we should know better, so instead of joining the hype, let's keep a cool head and educate people about what this is and what it isn't.
On a flip note: the game is fun enough.
Nevermind that this perfectly describes 90% of software development.
I'm actually wondering to what extent these responses are fueled by fear of being replaced by AI.
I don't understand what's so at stake with this that you feel like people are afraid. It's fun and amazing it can spit out stuff like this, and if you are a good developer experimenting with this stuff you already know its inarguably a novel and useful utility, if still limited in some ways.
But where is the fire? Why does everything got to devolve into one vague culture war or another? Shouldn't you welcome good faith critique? If only for the fact that these things can still be improved, and how can you hope to improve them if you smother and dismiss every suggestion that these models might be less than perfect.
That being said, I don't think saying that the model outputs information from its training set adds a lot to the discussion because -- and that's my point -- the same is true for human software developers most of the time (yes, the 90% is a made up number). This isn't meant at all to criticize the skills of the developers, but rather point out that most of our work is just much less interesting than we'd like it to be, and could be automated.
Also, I don't think developers will be replaced by AI, just like they were not replaced by code generators, build scripts, IDE auto-complete, IDE rename all usages, and so on. What might happen is that they will no longer have to write mind-numbing boilerplate code, which IMHO is a good thing.
The prompt I've seen for it to verbatim reproduce the fast inverse square root from Quake was:
// fast inverse square root
float Q_
So, my original thought was that the prompt above with the characteristic Quake III Q_ naming is enough to push it into a corner where the path is reduced to just one possibility (with that path being the words in the code itself) and not that it merely copypasted the code from an encoded version of it. I.e. it still predicts it word-by-word but with only one possible way for each step. This is just be my naive take on it though but I really want to understand.
This is what people mean when they say it copy pastes things. It doesn't literally go to the source code, press ctrl-c and then ctrl-v that to you, nobody believes it did.
And the model does this a lot, as I said the reason it doesn't do that all the time is that they train it not to. And the quake code example got such a big deal that they started to hard code it to not return that, but that doesn't mean it never does that for other things, just that this particular example is now "fixed".
The Quake code example still works in Copilot so I don't think they did anything about it, but only if I use the Q_ trick.
"give me C code for calculating the fast inverse square root of a number, do not explain yourself"
again resulted in the original function, comments included. Today it generates a completely different result and interestingly opts to explain the origin of the technique despite the directive for it to not explain itself.
Even if it was, what would we search for?
I was hoping someone would find a reference on wikipedia or something, which would clearly be part of the training set.
Sudoku at the hardest difficulty also has this, but usually the errors manifest a bit more quickly. It feels in this mode you could end up finding your error 'at the end' and have an absolutely diabolical time debugging your error?
very large totals gives you enough information to validate/eliminate numbers too
Master I've no idea how to solve
Keep fixing digits one at a time with things like parity, e.g. if the numbers are all odd and sum to an odd number, you know an odd number of them are needed. If a total is very high or low, there's often obviously only one way to make it. For totals not quite so high, if you choose the few highest numbers, and by trying ways to reduce the total by the excess, it becomes evident what the numbers are. ("Get your hands dirty.")
Often a row/column contains e.g. two 7s, and you know one of them is needed, but not which until other information comes in. (Having an "OR" label/symbol to mark those would be nice I guess.)
e.g. One of the columns I had: total 46, column is 16,-2,12,-2,14,-2,14,16,1. Eliminate the 1 by parity. I try adding the largest numbers, 16,16,14, which add to 46...and somehow I can see/intuit that there's no other way of making 46, as the -2s can only adjust downwards. So you green-circle the two 16s, leave the two 14s blank, as you don't know which is needed yet, and cross out all the others.
Sudoku Rule: Don’t Guess
Sudoku Rule: Unique Solution
You aren't supposed to guess at any point, instead solving the puzzle by determining a number's position by logical deduction. You aren't supposed to just jot something down and hoping for the best.
Each sudoku puzzle should have one single valid solution. This has been used in the past by a devious creator that built his sudoku in such a way that the final n numbers to be filled led to two deduction paths; one leading to a single solution, the other to two possible solutions. As such, the only valid solution is the path where uniqueness remained.
I didn't look at the code for Sumplete, but using similar rules when building the puzzle seems obvious.
I don't see how this differs from there being three solutions, thereby not following the unique solution role.
Like, what is functionally the difference between picking the path that leads to one solution rather than two, and just picking one of the two solutions at the end?
It's worth noting that "don't guess" technically doesn't change anything at all - a full exhaustive search of all options starting from the top-left corner is a legitimate logical deduction tactic (and a legitimate proof in mathematics), even if suboptimal. If you eliminate all the possibilities of writing in numbers, you're supposed to be left only one way that fits the rules, the unique solution.
I don't know what the AI will or will not be able to do, but what's clear is that things are not going to be the same any longer.
New Jobs:
- AI Prompt Engineer.
- AI Prompt Analyst.
- AI Prompt Architect.
If you kind of understand how the prediction works, you're likely able to become quite good prompting it to generate mostly functional things.I really believe a lot of the articles we see here are people doing just that, understanding how the tool works, then getting 80% of the way to something functional , then using actual programming knowledge to make things work.
I do think as others have said, this puzzle game has already existed so nothing was really invented, but...how would you know that if you didn't know the name or the format of the original puzzle game.
I really recommend trying to get through this if you can: https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-...
It raises some questions for me about how far this current model can actually scale / evolve without getting a bit too far out to be useful for human use. But it can (sometimes) connect things in ways that people have likely never seen before.
Maybe if you just clicked the button all day, you'd wind up with some really impressive new games people have never seen before.
That doesn't mean it won't regurgitate preexisting material (ask it to recount the constitution, for example), but it can definitely connect words in way that describes novel ideas.
If the internet is America the continent, where are lots of humans work, you can call the colonization as a genocide to native americans, or stealing the land with honor.
I’ve been experimenting with the depth of “prompt engineering”
I basically prompted it to procedurally generate rooms and fill them with NPCs with a common goal, on its own it persists the NPC names, genders, talking style, and the goal of the puzzle even though each region of the puzzle are procedurally generate
I will absolutely slap an 8-bit GUI on top of that
Here's the screenshot -- of the four remaining sixes, either of the two diagonally-opposite pairs should work (top-left and bottom-right or top-right and bottom-left):
https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi...
Another problem is of course the not evenly levels of difficulties with the same block size.
- Ability to mark cells as "locked" (i.e. "definitely present"). It's hard to play it on a larger grid since you have to keep it all in your head - Built in calculator of some sort where you could multi-select a few cells and it would show their sum somewhere. Otherwise it's too much arithmetics to do manually
Try double clicking
A common misconception. Legally, the game was invented by the OP through the use of prompt engineering. The op retains copyright for it. A machine cannot hold invention rights or copyright anymore than a camera can claim copyright for a photo "it" took with your help.
OP might be able to claim copyright, but OP did not invent the rules or write the code.
People are mad that headline over-exagerrates the impressive performance.
The solution is not unique, I just found one puzzle where I have
8----8
| |
| |
8----8
now i'm really worried :)))))
The game:
"""
Sure, I can give it a try! Here's a logic puzzle game that I came up with:
Title: Pathfinder
Objective: The objective of the game is to fill a grid with numbers from 1 to N (N is determined by the size of the grid), such that each number appears exactly once in each row, column, and diagonal, and also such that the numbers create a continuous path throughout the grid.
Rules:
The grid is a square grid of size N x N. The grid is divided into different regions, each representing a different terrain or landscape (e.g. forest, desert, ocean, mountain, etc.). Each region has a specific starting and ending point, represented by two numbers on the edge of the grid. The numbers in the grid must form a continuous path connecting the starting and ending points of each region, without ever intersecting or overlapping with itself. The numbers in the path must also satisfy the rules of Sudoku, meaning that each number must appear exactly once in each row, column, and diagonal of the grid. Example: Here's an example of a Pathfinder puzzle for a 5x5 grid:
| | | | 9 | |
| | | | | 7 |
| | | 3 | | |
| | | | | |
| | 2 | | | |
First:
As an AI language model, I am not able to provide a working code with HTML and JavaScript.
Example:
// Generate the puzzle board and regions
function generatePuzzle() {
let size = 5; // Change this to adjust the size of the grid
let board = new Array(size);
for (let i = 0; i < size; i++) {
board[i] = new Array(size);
for (let j = 0; j < size; j++) {
board[i][j] = 0;
}
}
let regions = generateRegions(size);
// Generate a path that connects all of the regions
let path = generatePath(regions, size);
// Fill in the grid with the numbers from the path
let index = 0;
for (let i = 0; i < size; i++) {
for (let j = 0; j < size; j++) {
if (path[i][j] !== 0) {
board[i][j] = path[i][j];
} else {
board[i][j] = "";
}
}
}
// Display the board and regions on the page
let grid
Did you try to get different games generated? I wonder if you'd get the same game as in the article at some point.
I am sure someone is already working on a ChatGPTOps
create a terraform template to create a brand new aws account from scratch, and then set up and admin account and two users named alice and bob.
This is what it output:
https://gist.github.com/jedberg/dd31783e13521a69aa8923cb5142... (which at quick glance looks correct)
It then said: " Note that you will need to have appropriate permissions and credentials to create a new AWS account, and this template assumes that you have those."
So I asked it how to get those permissions and it gave me step by step instructions on creating a new account, adding a payment method, and getting the root keys.
Then I asked it how to run the terraform and it gave me the commands to do it.
So I'd say yes, it can do DevOps too!