Transformers and diffusion models are not the same, even if they use related math
Edit: By the magic of advanced mathematics, every Turing complete structure can be rewritten into any other Turing complete structure with no loss of function or change in behavior
So the logic “remove one” will remove all of modern computing because the AI companies are not giving to their models. If they have to start pretending they aren’t neural network anymore they will.
And if you DON’T rewrite, then you’re back to them actually being different again
This is a dumb take. You can use a more general term like large dataset generative machine learning. Legislation needs to understand the different risks between the different implementations to do any good.
Machine B has now been fully rewritten to structures that are no longer a neural network. Everything it learned has been extracted from the model and given a new form. It doesn’t even run on a GPU anymore.
Its just decision trees and explicit function now. Same origin, same behavior, wildly different implementation and appearance. It just looks like another program. Especially to a judge.
Every rule you wrote that specified “neural”, not something more universal as “heuristic”, has now been denied by the judge, as you do not have jurisdiction against the new thing.
This isn’t some academic wordplay either. All machine implementable logic has infinitely many possible representations. If you specify your rule on appearance, not behavior, then the appearance will change and the behavior stays.
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LLMs is a subset of generative AI, but an image generator as an example is not a LLM
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Transformers and diffusion models are not the same, even if they use related math
Edit: By the magic of advanced mathematics, every Turing complete structure can be rewritten into any other Turing complete structure with no loss of function or change in behavior
So the logic “remove one” will remove all of modern computing because the AI companies are not giving to their models. If they have to start pretending they aren’t neural network anymore they will.
And if you DON’T rewrite, then you’re back to them actually being different again
https://infosec.pub/comment/23830616
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This is a dumb take. You can use a more general term like large dataset generative machine learning. Legislation needs to understand the different risks between the different implementations to do any good.
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https://arxiv.org/abs/2608.29530
https://link.springer.com/article/10.1023/A:1009670302979
https://proceedings.neurips.cc/paper/2020/file/e4acb4c86de9d2d9a41364f93951028d-Paper.pdf
https://arxiv.org/html/2106.03354v3
https://luke-griffiths.github.io/non-neural-networks/
Machine B has now been fully rewritten to structures that are no longer a neural network. Everything it learned has been extracted from the model and given a new form. It doesn’t even run on a GPU anymore.
Its just decision trees and explicit function now. Same origin, same behavior, wildly different implementation and appearance. It just looks like another program. Especially to a judge.
Every rule you wrote that specified “neural”, not something more universal as “heuristic”, has now been denied by the judge, as you do not have jurisdiction against the new thing.
This isn’t some academic wordplay either. All machine implementable logic has infinitely many possible representations. If you specify your rule on appearance, not behavior, then the appearance will change and the behavior stays.