15 years ago people made fun of AI models because they could mistake some detail in a bush for a dog. Over time the models became more resistant against those kinds of errors. The change was more data and better models.
It’s the same type of error as hallucination. The model is overly confident about a thing it’s wrong about. I don’t see why these types of errors would be any different.
I don’t see why these types of errors would be any different.
Well it is easy to see when you understand what LLMs actually do and how it is different from what humans do. Humans have multiple ways to correct errors and we do it all the time, intuitively. LLMs have none of these ways, they can only repeat their training (and not even hope for the best, because to hope is human again)
I’m extrapolating from history.
15 years ago people made fun of AI models because they could mistake some detail in a bush for a dog. Over time the models became more resistant against those kinds of errors. The change was more data and better models.
It’s the same type of error as hallucination. The model is overly confident about a thing it’s wrong about. I don’t see why these types of errors would be any different.
Well it is easy to see when you understand what LLMs actually do and how it is different from what humans do. Humans have multiple ways to correct errors and we do it all the time, intuitively. LLMs have none of these ways, they can only repeat their training (and not even hope for the best, because to hope is human again)