It stands to reason that if you have access to an LLM’s training data, you can influence what’s coming out the other end of the inscrutable AI’s network. The obvious guess is that…
Then you have to create a framework for evaluating the effect of the addition of each source into “positive” or “negative”. Good luck with that. They can’t even map input objects in the training data to their actual source correctly or consistently.
It’s absolutely possible, but pretty much anything that adds more overhead per each individual input in the training data is going to be too costly for any of them to try and pursue.
O(n) isn’t bad, but when your n is as absurdly big as the training corpuses these things use, that has big effects. And there’s no telling if it would actually only be an O(n) cost.
Yeah, after reading a bit into it. It seems like most of the work is up front, pre filtering and classifying before it hits the model, to your point the model training part is expensive…
I think broadly though, the idea that they are just including the kitchen sink into the models without any consideration of source quality isn’t true
I’m sure that’s true, but it is also noteworthy that any and every consideration that goes into the initial inclusion of the data before it is fed into the model introduces intended and unintended consequences on the training.
Furthermore, the proliferation of the LLMs themselves is putting negative pressure on survival of the places where all the good data is sourced from in the first place. When traffic to a place like stackoverflow is way down because everyone’s reading LLM answers (that the LLM training dataset got from stack overflow), there are less good conversations on stackoverflow to read. Some of these sources of training data may even be caused to cease to exist entirely.
Then you have to create a framework for evaluating the effect of the addition of each source into “positive” or “negative”. Good luck with that. They can’t even map input objects in the training data to their actual source correctly or consistently.
It’s absolutely possible, but pretty much anything that adds more overhead per each individual input in the training data is going to be too costly for any of them to try and pursue.
O(n) isn’t bad, but when your n is as absurdly big as the training corpuses these things use, that has big effects. And there’s no telling if it would actually only be an O(n) cost.
Yeah, after reading a bit into it. It seems like most of the work is up front, pre filtering and classifying before it hits the model, to your point the model training part is expensive…
I think broadly though, the idea that they are just including the kitchen sink into the models without any consideration of source quality isn’t true
I’m sure that’s true, but it is also noteworthy that any and every consideration that goes into the initial inclusion of the data before it is fed into the model introduces intended and unintended consequences on the training.
Furthermore, the proliferation of the LLMs themselves is putting negative pressure on survival of the places where all the good data is sourced from in the first place. When traffic to a place like stackoverflow is way down because everyone’s reading LLM answers (that the LLM training dataset got from stack overflow), there are less good conversations on stackoverflow to read. Some of these sources of training data may even be caused to cease to exist entirely.