It’s not AI, it’s neural network models in the same way voice recognition in devices has been working for over a decade. Even Dragon has been utilizing language models vectors for a very long time, just requiring voice training instead of utilizing a premade research or open-source data set.
I hate generative AI and it’s slop too, but getting angry about neural network models in general is not only absurd, but playing exactly into what corporations want – conflation of the underlying basic technology concepts with the capitalistic vampirism of art.
EDIT: to add, “research” here can be closed source – voice models utilized with these tend to be internally-sourced for much of them, at least earlier ones do.
But much more loosely-so, not nearly as heavily. It was more like a seldom-used term to say that it might be like what machine learning actually was.
Now they’re all being called it heavily, forcefully, by corporations which started using it for capitalistic hype reasons. Hence, the push for strong distinctions between a field that’s been around for quite a while as algorithms in mathematics being a variety of types, and lazy slop that “just one more prompt bro” and “we can replace workers”. Even DLSS wasn’t called “AI” until the hype train started, and now Jensen Huang can’t call it that often enough lest he be unable to afford yet another leather jacket as if they’re disposable glasses wipes.
It’s not AI, it’s neural network models in the same way voice recognition in devices has been working for over a decade. Even Dragon has been utilizing language models vectors for a very long time, just requiring voice training instead of utilizing a premade research or open-source data set.
I hate generative AI and it’s slop too, but getting angry about neural network models in general is not only absurd, but playing exactly into what corporations want – conflation of the underlying basic technology concepts with the capitalistic vampirism of art.
EDIT: to add, “research” here can be closed source – voice models utilized with these tend to be internally-sourced for much of them, at least earlier ones do.
These used to be called AI before people decided that only LLMs and Diffusion models were AI. Both of which are types of neural networks.
But much more loosely-so, not nearly as heavily. It was more like a seldom-used term to say that it might be like what machine learning actually was.
Now they’re all being called it heavily, forcefully, by corporations which started using it for capitalistic hype reasons. Hence, the push for strong distinctions between a field that’s been around for quite a while as algorithms in mathematics being a variety of types, and lazy slop that “just one more prompt bro” and “we can replace workers”. Even DLSS wasn’t called “AI” until the hype train started, and now Jensen Huang can’t call it that often enough lest he be unable to afford yet another leather jacket as if they’re disposable glasses wipes.