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<blockquote data-quote="mamba" data-source="post: 9272680" data-attributes="member: 7034611">They are entirely different. The random generator follows a set of predefined rules and picks predefined options from a pool at random within the confines of those rules.No one knows what an AI does, seriously… we know how to create one, we know how to train it (reward it for good results, so it can adjust its internal logic to more reliably produce results we like), but how it actually determines what output to show us for a given input is a black box, no one knows how it gets to its results.Without training on a wide dataset the AI is just a moron that randomly picks stuff and presents it as the result. It first has to learn what things are (eg when you ask for a picture of a penguin, for you to then get something that looks like a penguin and not a car or mountain lake). It does not really understand what a penguin is though, but it does understand that if you ask it for one and it shows you some upright black and white figure standing in snow, you are probably happy with that result.A large dataset and extensive training are needed to get ‘reliable’ results and not just random garbage.For us to understand how AIs get to their results there is the Explainable AI idea, which aims at having AIs that tell us how they arrived at their conclusions, but that is still pretty new <img src="https://cdn.jsdelivr.net/joypixels/assets/8.0/png/unicode/64/1f609.png" class="smilie smilie--emoji" loading="lazy" width="64" height="64" alt=";)" title="Wink&nbsp; &nbsp; ;)"&nbsp; data-smilie="2"data-shortname=";)" />TL,DR: random generators follow rules established by the programmer, an AI comes up with and keeps refining its own rules based on how much we like its output for a given input</blockquote>

[QUOTE="mamba, post: 9272680, member: 7034611"] They are entirely different. The random generator follows a set of predefined rules and picks predefined options from a pool at random within the confines of those rules. No one knows what an AI does, seriously… we know how to create one, we know how to train it (reward it for good results, so it can adjust its internal logic to more reliably produce results we like), but how it actually determines what output to show us for a given input is a black box, no one knows how it gets to its results. Without training on a wide dataset the AI is just a moron that randomly picks stuff and presents it as the result. It first has to learn what things are (eg when you ask for a picture of a penguin, for you to then get something that looks like a penguin and not a car or mountain lake). It does not really understand what a penguin is though, but it does understand that if you ask it for one and it shows you some upright black and white figure standing in snow, you are probably happy with that result. A large dataset and extensive training are needed to get ‘reliable’ results and not just random garbage. For us to understand how AIs get to their results there is the Explainable AI idea, which aims at having AIs that tell us how they arrived at their conclusions, but that is still pretty new ;) TL,DR: random generators follow rules established by the programmer, an AI comes up with and keeps refining its own rules based on how much we like its output for a given input [/QUOTE]

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