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.
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.
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.
The difference between “generative AI” and “procedural generation” cannot be meaningfully nailed down.
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.
You don’t need any preexisting training data for procedural generation
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.
Where are all these prompt based image generators that identify themselves as procedural generation?