Well now. I'm open to taking the first part at face value, but the second part of that instruction does raise some questions.
Well now. I'm open to taking the first part at face value, but the second part of that instruction does raise some questions.
FWIW asking LLMs about their training data is generally HEAVILY prone to inaccurate responses. They aren't generally told exactly what they were trained on, so their response is completely made up, as they're predicting the next token based on their training data, without knowing what they data was - if that makes any sense.
Let's say it was only trained on the book 1984. It's response will be based on what text would most likely be next from the book 1984 - and if that book doesn't contain "This text is a fictional book called 1984", instead it's just the story - then the LLM would be completing text as if we were still in that book.
tl;dr - LLMs complete text based on what they're trained with, they don't have actual selfawareness and don't know what they were trained with, so they'll happily makeup something.
EDIT: Just to further elaborate - the "innocent" purpose of this could simply be to prevent the model from confidently making up answers about it's training data, since it doesn't know what it's training data was.
Hardly any of the training data exists in the context of the word “training data”, unless databricks are enriching their data with such words.
It has something to do with it. There will be scenarios where the definition of "copyrighted material" does matter, even if they come up relatively infrequently for Databricks' intended use cases. If I ask DBRX directly whether it was trained on copyrighted material, it's quite likely to (falsely) tell me that it was not. This seems suboptimal to me (though perhaps they A/B tested different prompts and this was indeed the best).
Also, the difference between "uncopyrighted" and "permissively licensed in the creative commons" is nuance that is not necessary for most conversations and would be a waste of attention neurons.
<testing new explanatory metaphor>
Remember an LLM is just a language model, it says whatever comes next without thought or intent. There's no brain behind it that stores information and understands things. It's like your brain when you're in "train of thought" mode. You know when your mouth is on autopilot, saying things that make sense and connect to each other and are conversationally appropriate, but without deliberate intent behind them. And then eventually your conscious brain eventually checks in to try to reapply some intent you're like "wait what was I saying?" and you have to deliberatly stop your language-generation brain for a minute and think hard and remember what your point was supposed to be. That's what llms are, train-of-thought with no conductor.
</testing new explanatory metaphor>
You can say that you have fair use to the work, or a license to use the work, or that the work is itself a "collection of facts" or "recipe" or "algorithm" without a creative component and thus copyright does not apply.
Part 2. Lie more
This feels like the Napster phase. We are free to do whatever until regulation creeps in to push control away from all and up the hierarchy.
All we need is Getty Images or some struggling heroin addicted artist on Vice finding their work used in OpenAIs to really trigger political spectrums.