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Gaywallet (they/it) ( Gaywallet@beehaw.org ) A to Gaming · 2 years ago

New AI model can hallucinate a game of 1993’s Doom in real time

arstechnica.com

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  • technology@lemmy.zip
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New AI model can hallucinate a game of 1993’s Doom in real time

arstechnica.com

Gaywallet (they/it) ( Gaywallet@beehaw.org ) A to Gaming · 2 years ago
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  • cross-posted to:
  • technology@lemmy.zip
Dobos: "Why write rules for software by hand when AI can just think every pixel for you?"
  • Even_Adder ( Even_Adder@lemmy.dbzer0.com ) 
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    2 years ago

    Do you have any examples of how they fail? There are plenty of ways to explain new concepts to models.

    https://arxiv.org/abs/2404.19427 https://arxiv.org/abs/2406.11643 https://arxiv.org/abs/2403.12962 https://arxiv.org/abs/2404.06425 https://arxiv.org/abs/2403.18922 https://arxiv.org/abs/2406.01300

    • MentalEdge ( MentalEdge@sopuli.xyz ) 
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      2 years ago

      In a couple sentences? In a way that doesn’t approach, equal or exceed the effort of training the model with that data to begin with?

      You insist these models can do new things out of nothing, and you keep saying “all you have to do, is give them something”.

      • Even_Adder ( Even_Adder@lemmy.dbzer0.com ) 
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        2 years ago

        You keep moving the goal posts and putting words in my mouth. I never said you can do new things out of nothing. Nothing I mentioned is approaching, equaling, or exceeding the effort of training a model.

        You haven’t answered a single one of my questions, and you are not arguing in good faith. We’re done here. I can’t say it’s been a pleasure.

        • MentalEdge ( MentalEdge@sopuli.xyz ) 
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          2 years ago

          My argument was and is that neural models don’t produce anything truly new. That they can’t handle things outside what is outlined by the data they were trained on.

          Are you not claiming otherwise?

          You say it’s possible to guide models into doing new things, and I can see how that’s the case, especially if the model is a very big one, meaning it is more likely that it has relevant structures to apply to the task.

          But I’m also pretty damn sure they have insurmountable limits. You can’t “guide” and LLM into doing image generation, except by having it interact with an image generation model.

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