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.
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.
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.
Nonsense. Procedural generation is a rule-based deterministic system while generative AI is probabilistic and data driven. It’s fundamentally different.
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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.
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Where are all these prompt based image generators that identify themselves as 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.
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.
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It’s less of a functional different and more of a moral one.
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