LLMs are more or less "trained on" everything, so saying that is rather pointless.
But it's wrong because yes, it does depend on whether a model thinks it (generates, RNG, whatever prefabricated pedantry you want), because that's what shapes the output. If it doesn't "think" something, it cannot use the training data.
And yea we all know that "think" here means to generate a set of tokens from a set of input with some temperature factor, leading to certain outputs which it then reingests to preform chain of thought (recursive self token generating).
But thinking accurately captures what OP said, and is understood by all.
LLMs are more or less "trained on" everything, so saying that is rather pointless.
But it's wrong because yes, it does depend on whether a model thinks it (generates, RNG, whatever prefabricated pedantry you want), because that's what shapes the output. If it doesn't "think" something, it cannot use the training data.
And yea we all know that "think" here means to generate a set of tokens from a set of input with some temperature factor, leading to certain outputs which it then reingests to preform chain of thought (recursive self token generating).
But thinking accurately captures what OP said, and is understood by all.