It’s Luna, their small, low-intelligence model. But still impressive to see.
I also found this screenshot on Reddit:
The model spent 26 seconds for some reason 🤔
It’s Luna, their small, low-intelligence model. But still impressive to see.
I also found this screenshot on Reddit:
The model spent 26 seconds for some reason 🤔
Kind of but not really. AIs learn to predict text but they can’t really do math the traditional way. They learn the tokens, which are more than syllables and less than a word long. So because they don’t do math, LLMs in particular speculate “something like 3 comes after this question” because in training it has seen similar questions answered with “3”. That’s the jist of it.
Your generalization, you see, doesn’t apply to what “Qwen27b” did here above, right ?
It doesn’t. I wouldn’t say I made a generalization but a very high level explanation so it’s easier to understand for non-tech people.
I suspect modern models are trained specifically on these kinds of questions to spare the embarrassment of this question for future models.
that does mean they stochastically understand the occurrence of other numbers for this question and if you wrote tokens similar to this it would answer with 4 or whatever the specific case. I’m just trying to explain that no matter whether it gets it right or wrong, it goes off of statistics and semantics, not math. Because these things are not made to do math, that’s what algorithms are for, and we know very well how to write them.
Yes he’s talking about why chatgpt failed the task