Comment on New AI model can hallucinate a game of 1993’s Doom in real time
MentalEdge@sopuli.xyz 3 months agoYou are completely missing what I’m saying.
Comment on New AI model can hallucinate a game of 1993’s Doom in real time
MentalEdge@sopuli.xyz 3 months agoYou are completely missing what I’m saying.
Even_Adder@lemmy.dbzer0.com 3 months ago
What kind of creativity are you talking about then? I’ve also never heard of a bloated model. Which models are bloated?
MentalEdge@sopuli.xyz 3 months ago
Bloated, as in large and heavy. More expensive, more power hungry, less efficient.
I already brought it up. They can’t deal with something completely new.
When you discuss what you want with a human artist or programmer or whatever, there is a back and forth process where both parties explain and ask until comprehension is achieved, and this improves the result.
It doesn’t matter if the programmer has played games with regenerating health before, one can comprehend and implement the concept based on just a couple sentences.
Now how would you do the same with a “general” model that didn’t have any games that works like that in the training data?
My point is that “general” models aren’t a thing. Not really. We can make models that are really, really big, but they remain very bad at filling in gaps in reality that weren’t in the training data. They don’t start magically putting two and two together and comprehending all the rest.
Even_Adder@lemmy.dbzer0.com 3 months ago
Do you have any examples of how they fail? There are plenty of ways to explain new concepts to models.
arxiv.org/abs/2404.19427 arxiv.org/abs/2406.11643 arxiv.org/abs/2403.12962 arxiv.org/abs/2404.06425 arxiv.org/abs/2403.18922 arxiv.org/abs/2406.01300
MentalEdge@sopuli.xyz 3 months ago
In a couple sentences? In a way that doesn’t equal or exceed the effort of training the model with that data to begin with?