Pocketpair Publishing boss John Buckley says we're already starting to see a flood of 'really low-quality, AI-made games' on Steam and other storefronts.
Derivative IP is so fucking different from gen AI. It’s stupid IP laws that force what could have been a commercial fangame to instead be legally distinct.
Nintendo wasn’t “inspired” by shit. They made an ice cream cone a Pokémon. Keys on a ring? Pokémon. 8 varieties of elemental flavored dog? Check. Oh hey cool look a 2d image on a computer oh wait it’s actually a Pokémon. Dog? Cat? Snake? Bird? Horse? All Pokémon. IMO nothing in Pokémon is actually “inspired”, only ripped off.
Is Mickey Mouse uncreative because it’s just a mouse? Is Yogi Bear uncreative because it’s just a bear?
Is Sherlock Holmes uncreative because it’s just a British guy? Especially if giving things magical abilities doesn’t count, then vampires, zombies, magicians, pretty much the entirety of fantasy is just “ripping off” humans. You think Tolkien was a good writer? You fool- the Ents are just trees, how boring! Gandald is just an old human, frodo is just a short dude!
So what does that leave that is original? Should all of our ficitiln need entirely new ideas? Do our writers need to invent new qwarks and new rules for how they interact, so that fictional universes can have different elements where we can imagine life forms without carbon that interact? Would it still be derivative to you if we keep the strong nuclear force the same in this fictional universe?
Inspiration is taking your peanut butter and putting it in my chocolate. You can’t just take the chocolate slap some eyes on it, and call it chocomon. Make it do cool shit like turn into a giant angel or trex or some shit like a properly inspired pocket monster. Or make a funny little blue slime guy and give him apocalypse level magic spells or something. Yeah
That sounds good.
Yeah because they spent money making it. If you spend millions of dollars making a video game, you can’t just shut it down and refund every order of it without putting your studio in serious jeopardy financially. That’s not an option for them, so the best they can do is just not rely on AI anymore. Clearly they tried it and learned that it actually sucks ass.
They’re currently being sued by Nintendo and palworld did not make anywhere near the kind of money that would let them survive a lawsuit AND a game cancellation.
You’re making assumptions about their financials that are only ever true for enormous studios like epic games, which pocketpair is not. The gaming industry does not operate as simply as you think it does and companies don’t have the freedom to throw money away on something as simple as virtue signaling.
It doesn’t matter if a company used AI back in 2022 when it was new and less understood; it matters what companies choose now. If you’re going to throw blind skepticism at them for not making arbitrary financial risks just to appease you, then you’re not worth appeasing anyway because you’re too cynical to be a potential customer.
I think it could work to give dynamic and varied answers to secondary characters given good prompts and other guardrails to preserve the immersion. As long as the core elements of the games are not AI generated slope, and developers are honest about where it was used.
As an amateur game dev, I believe AI will crash out for the public before it becomes truly useful for programming. I’ve heard colleagues try to use AI , but it often just creates more work. When the AI doesn’t know the answer, which is often. it makes something up, leading to errors, crashes, or hidden issues like memory leaks. I’d rather write the code correctly from the start and understand how it works, than spend hours hunting down problems in AI-generated code, only to never find the issue. Full disclosure I use Chatgpt to edit my dialogue as my English is not great.
Your anecdote checks out with a study I heard about. Office teams that were using LLMs for a few months reported that results are faster, but editing took longer than doing it conventionally in the first place. Generating boiler plate code and documentation could be another very useful use case in software dev, and I don’t really care if that’s used. Like in your use case, spell/grammar checking, using LLMs is a natural development of the tools that we already had. Your text processors marks errors, who cares if it’s powered by an LLM or by a huge heuristic rule set?
I am using them as a side tool for development. I think LLMs are already very performent for web knowledge search (e.g. replacing a search on stackoverflow), suggestions, explanations and error detection. Although is it worth the resources consumption? Not sure, but I can’t afford not staying on top of the tooling available for my job. However, I agree, in my experience, the edit/agent modes are not efficient for coding, for now.
Generating secondary dialogues for a video game is quite a lower quality requirement than software engineering. So I think it could work there. It requires sounding natural, not being exact, LLMs are good at this.
yeah for low stakes how-tos I’ve been asking more and more using one of the free LLMs. For higher stakes I ask for their sources if they can give it and go from them on my own.
It’s been really nice to be able to type a plain question (in any language) into Google and receive a concise answer before scrolling down to confirm with more trustworthy sources. In particular it’s been very good for solving annoyances with UI options by directing me to exactly what I’m looking for. A traditional search will often conflate my search with synonyms (even when using quotations, which is some bullshit), and even ignore what language my search was in.
e: Also you should be careful when clicking on any links provided by an LLM because they can accidentally send you phishing links.
SEO destroyed google’s usefulness. AI is a cope for that but AI kills the incentives for very thing it depends on for it’s usefulness, user generated content.
My anecdote for AI and coding is that it’s a good replacement for google searching, especially when you are learning a new language.
You need to understand the fundamentals first, but asking the AI how to do a task in C when you’ve only coded in JS is very helpful. It’s still wrong, but it’s not like Stack Overflow is more accurate.
You’d think that that’s the one thing LLMs should be good at – have characters respond to arbitrary input in-character according to the game state. Unfortunately, restricting output to match the game state is mathematically impossible with LLMs; hallucinations are inevitable and can cause characters to randomly start lying or talking about things thy can’t know about. Plus, LLMs are very heavy on resources.
There are non-generative AI techniques that could be interesting for games, of course; especially ones that can afford to run at a slower pace like seconds or tens of seconds. For example, something that makes characters dynamically adapt their medium-term action plan to the situation every once in a while could work well. But I don’t think we’re going to see useful AI-driven dialogue anytime soon.
You seem to imply we can only use the raw output of the LLm but that’s not true. We can add some deterministic safeguards afterwards to reduce hallucinations and increase relevancy. For example if you use an LLM to generate SQL, you can verify that the answer respects the data schemas and the relationship graph. That’s a pretty hot subject right now, I don’t see why it couldn’t be done for video game dialogues.
Indeed, I also agree that the consumption of resources it requires may not be worth the output.
It would not be a fully determining schema that could apply to random outputs, I would guess this is impossible for natural language, and if it is possible, then it may as well be used for procedural generation. It would be just enough to make an LLM output be good enough. It doesn’t need to be perfect because human output is not perfect either.
I am really praying for the day corporate drops this foolish nonsense of foisting it on their company and employees - maybe even gasp enabling their teams to access and use the tools that help them do better and more creative jobs.
Because AI can fit into a lot of people’s toolsets really nicely, especially in creative fields like game design. Just need to drop the idea that AI is an authoritative final answer to our design problems and instead realize that it’s just another tool to help us get to those solutions.
Neural networks are deterministic. In LLMs, it outputs probabilities, which are picked from via seeded RNG. Image generation tries multiple options based on different seeds, then picks the best fit as identified by a neural network and repeats. For both, if you give a specific model the same inputs, you’ll get the same output.
The public-facing interfaces don’t give seed control, which means they give a different output each time, but that isn’t an inherent property of generative AI.
I think it can - procedural generation consist of procedures, that is elements designed by humans, which are just connected into a bigger structure. Every single template, rule and atomic object (e.g. a single room in a generated house) is hand-designed, and as such no matter what comes out the elements and connections were considered by a real human. On the other hand, generative AI is almost always some sort of machine learning, that is an approximation of what a good structure of something should be, but it is only a very poor, randomised approximation. You have absolutely no guarantees nor constraints on what might pop out of the model - that is my main concern with genAI, though the whole outputted thing looks reasonable, upon closer inspection it has a lot of inconsistenties.
I think you are reading in the “designed by humans” part. Even when that is nominally true, the whole point of procedural generation is to create a level of complexity and emergence that the outputs are surprising and novel. Things no one expected are desirable. I think the distinction being drawn is not meaningful; in both cases, it is entirely possible and likely that no human being understands how a given output was arrived at.
Nonsense. Procedural generation is a rule-based deterministic system while generative AI is probabilistic and data driven. It’s fundamentally different.
Markov chains are both probabilistic and data-driven. For example. LLMs are not that far removed from markov chains. Should game developers be allowed to use latent spaces or is that too sloppy AI?
Okay, but (ignoring that procedural generation can also be probabilistic) what is the functional difference? The point I’m getting at is that you cannot banish the one without necessarily limiting the other.
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“We might deal in derivative IP, but it’s our derivative IP!”
Derivative IP is so fucking different from gen AI. It’s stupid IP laws that force what could have been a commercial fangame to instead be legally distinct.
To be fair Nintendo was heavily inspired by other artists work when designing Pokemon.
Nintendo wasn’t “inspired” by shit. They made an ice cream cone a Pokémon. Keys on a ring? Pokémon. 8 varieties of elemental flavored dog? Check. Oh hey cool look a 2d image on a computer oh wait it’s actually a Pokémon. Dog? Cat? Snake? Bird? Horse? All Pokémon. IMO nothing in Pokémon is actually “inspired”, only ripped off.
What a silly thing to say.
Is Mickey Mouse uncreative because it’s just a mouse? Is Yogi Bear uncreative because it’s just a bear?
Is Sherlock Holmes uncreative because it’s just a British guy? Especially if giving things magical abilities doesn’t count, then vampires, zombies, magicians, pretty much the entirety of fantasy is just “ripping off” humans. You think Tolkien was a good writer? You fool- the Ents are just trees, how boring! Gandald is just an old human, frodo is just a short dude!
So what does that leave that is original? Should all of our ficitiln need entirely new ideas? Do our writers need to invent new qwarks and new rules for how they interact, so that fictional universes can have different elements where we can imagine life forms without carbon that interact? Would it still be derivative to you if we keep the strong nuclear force the same in this fictional universe?
Inspiration is taking your peanut butter and putting it in my chocolate. You can’t just take the chocolate slap some eyes on it, and call it chocomon. Make it do cool shit like turn into a giant angel or trex or some shit like a properly inspired pocket monster. Or make a funny little blue slime guy and give him apocalypse level magic spells or something. Yeah That sounds good.
you forgot rock.
There’s Rock, Rock With Arms, and Big Rock Snake
Im casually suggesting they were “inspired” by other artists work. Many of the Red/Blue era were rip offs.
They made Goth Mommy GF into a pokemon with “Gothita”
How many sentient clouds are also pokemon? Or that one that’s literally just a balloon?
I swear pokemon ran out of creativity by gen 3 - and I’m not even a pokemon fan.
Derivative over generative any day if you ask me.
We don’t believe in AI, says the developer of AI Art Impostor
With how badly that game was received, maybe they understood the point. Maybe
Any relation to loss guy?
We’re all cousins, so probably?
Isn’t that Garfield’s owner
That’s Jon Arbuckle
But… The developers of Palworld made a game featuring AI generated images.
Companies can change their mind about stuff like this.
Yes. Except they’re still selling that game.
Yeah because they spent money making it. If you spend millions of dollars making a video game, you can’t just shut it down and refund every order of it without putting your studio in serious jeopardy financially. That’s not an option for them, so the best they can do is just not rely on AI anymore. Clearly they tried it and learned that it actually sucks ass.
It’s a small game. They have Palworld to rake in the big bucks, so if their stance on AI use has changed, they can just remove that game.
They’re currently being sued by Nintendo and palworld did not make anywhere near the kind of money that would let them survive a lawsuit AND a game cancellation.
You’re making assumptions about their financials that are only ever true for enormous studios like epic games, which pocketpair is not. The gaming industry does not operate as simply as you think it does and companies don’t have the freedom to throw money away on something as simple as virtue signaling.
It doesn’t matter if a company used AI back in 2022 when it was new and less understood; it matters what companies choose now. If you’re going to throw blind skepticism at them for not making arbitrary financial risks just to appease you, then you’re not worth appeasing anyway because you’re too cynical to be a potential customer.
I’m not making assumptions about their financial situation. I’m critical of their hypocrisy. I don’t care about the excuses.
Your expectations are too high and your cynicism is clouding your judgment.
I think it could work to give dynamic and varied answers to secondary characters given good prompts and other guardrails to preserve the immersion. As long as the core elements of the games are not AI generated slope, and developers are honest about where it was used.
As an amateur game dev, I believe AI will crash out for the public before it becomes truly useful for programming. I’ve heard colleagues try to use AI , but it often just creates more work. When the AI doesn’t know the answer, which is often. it makes something up, leading to errors, crashes, or hidden issues like memory leaks. I’d rather write the code correctly from the start and understand how it works, than spend hours hunting down problems in AI-generated code, only to never find the issue. Full disclosure I use Chatgpt to edit my dialogue as my English is not great.
I don’t think AI code generation is going to be a revolution anytime soon, but AI voice and AI image generation is likely going to stay.
Your anecdote checks out with a study I heard about. Office teams that were using LLMs for a few months reported that results are faster, but editing took longer than doing it conventionally in the first place. Generating boiler plate code and documentation could be another very useful use case in software dev, and I don’t really care if that’s used. Like in your use case, spell/grammar checking, using LLMs is a natural development of the tools that we already had. Your text processors marks errors, who cares if it’s powered by an LLM or by a huge heuristic rule set?
I am using them as a side tool for development. I think LLMs are already very performent for web knowledge search (e.g. replacing a search on stackoverflow), suggestions, explanations and error detection. Although is it worth the resources consumption? Not sure, but I can’t afford not staying on top of the tooling available for my job. However, I agree, in my experience, the edit/agent modes are not efficient for coding, for now.
Generating secondary dialogues for a video game is quite a lower quality requirement than software engineering. So I think it could work there. It requires sounding natural, not being exact, LLMs are good at this.
yeah for low stakes how-tos I’ve been asking more and more using one of the free LLMs. For higher stakes I ask for their sources if they can give it and go from them on my own.
It’s been really nice to be able to type a plain question (in any language) into Google and receive a concise answer before scrolling down to confirm with more trustworthy sources. In particular it’s been very good for solving annoyances with UI options by directing me to exactly what I’m looking for. A traditional search will often conflate my search with synonyms (even when using quotations, which is some bullshit), and even ignore what language my search was in.
e: Also you should be careful when clicking on any links provided by an LLM because they can accidentally send you phishing links.
SEO destroyed google’s usefulness. AI is a cope for that but AI kills the incentives for very thing it depends on for it’s usefulness, user generated content.
My anecdote for AI and coding is that it’s a good replacement for google searching, especially when you are learning a new language.
You need to understand the fundamentals first, but asking the AI how to do a task in C when you’ve only coded in JS is very helpful. It’s still wrong, but it’s not like Stack Overflow is more accurate.
You’d think that that’s the one thing LLMs should be good at – have characters respond to arbitrary input in-character according to the game state. Unfortunately, restricting output to match the game state is mathematically impossible with LLMs; hallucinations are inevitable and can cause characters to randomly start lying or talking about things thy can’t know about. Plus, LLMs are very heavy on resources.
There are non-generative AI techniques that could be interesting for games, of course; especially ones that can afford to run at a slower pace like seconds or tens of seconds. For example, something that makes characters dynamically adapt their medium-term action plan to the situation every once in a while could work well. But I don’t think we’re going to see useful AI-driven dialogue anytime soon.
You seem to imply we can only use the raw output of the LLm but that’s not true. We can add some deterministic safeguards afterwards to reduce hallucinations and increase relevancy. For example if you use an LLM to generate SQL, you can verify that the answer respects the data schemas and the relationship graph. That’s a pretty hot subject right now, I don’t see why it couldn’t be done for video game dialogues.
Indeed, I also agree that the consumption of resources it requires may not be worth the output.
If you could define a formal schema for what appropriate dialogue options would be you could just pick from it randomly, no need for the AI
It would not be a fully determining schema that could apply to random outputs, I would guess this is impossible for natural language, and if it is possible, then it may as well be used for procedural generation. It would be just enough to make an LLM output be good enough. It doesn’t need to be perfect because human output is not perfect either.
Yeah that’s kind of my point. That’s a vastly more complicated thing than SQL.
But it also doesn’t need to be as exact as SQL, which removes some kind of complexity.
I am really praying for the day corporate drops this foolish nonsense of foisting it on their company and employees - maybe even gasp enabling their teams to access and use the tools that help them do better and more creative jobs.
Because AI can fit into a lot of people’s toolsets really nicely, especially in creative fields like game design. Just need to drop the idea that AI is an authoritative final answer to our design problems and instead realize that it’s just another tool to help us get to those solutions.
The difference between “generative AI” and “procedural generation” cannot be meaningfully nailed down.
Procedural generation is theoretically deterministic, but it’s a fairly minor distinction.
Generative AI is too. Maintain your seed and you should get the same result every time.
Most of the SaaS AI tools don’t expose control over their RNG, but some self-hosted ones do.
Generative AI is by definition non deterministic.
Neural networks are deterministic. In LLMs, it outputs probabilities, which are picked from via seeded RNG. Image generation tries multiple options based on different seeds, then picks the best fit as identified by a neural network and repeats. For both, if you give a specific model the same inputs, you’ll get the same output.
The public-facing interfaces don’t give seed control, which means they give a different output each time, but that isn’t an inherent property of generative AI.
I think it can - procedural generation consist of procedures, that is elements designed by humans, which are just connected into a bigger structure. Every single template, rule and atomic object (e.g. a single room in a generated house) is hand-designed, and as such no matter what comes out the elements and connections were considered by a real human. On the other hand, generative AI is almost always some sort of machine learning, that is an approximation of what a good structure of something should be, but it is only a very poor, randomised approximation. You have absolutely no guarantees nor constraints on what might pop out of the model - that is my main concern with genAI, though the whole outputted thing looks reasonable, upon closer inspection it has a lot of inconsistenties.
I think you are reading in the “designed by humans” part. Even when that is nominally true, the whole point of procedural generation is to create a level of complexity and emergence that the outputs are surprising and novel. Things no one expected are desirable. I think the distinction being drawn is not meaningful; in both cases, it is entirely possible and likely that no human being understands how a given output was arrived at.
You don’t need any preexisting training data for procedural generation
Nonsense. Procedural generation is a rule-based deterministic system while generative AI is probabilistic and data driven. It’s fundamentally different.
Markov chains are both probabilistic and data-driven. For example. LLMs are not that far removed from markov chains. Should game developers be allowed to use latent spaces or is that too sloppy AI?
Okay, but (ignoring that procedural generation can also be probabilistic) what is the functional difference? The point I’m getting at is that you cannot banish the one without necessarily limiting the other.
It’s less of a functional different and more of a moral one.
Content theft is a separate issue. We can agree to ban the fruits of content theft without drawing arbitrary technical taboos.
Where are all these prompt based image generators that identify themselves as procedural generation?
🤣🤣🤣👌👍
Yeah the company that ripped off Nintendo (I couldn’t give two shits, don’t screech) totally hates AI 🤣👌👍.
Hello AI!