There’s a difference between predictions which can be reasonably ascertained from the inputs and those which cannot. No language model can tell you the outcome

There’s a difference between predictions which can be reasonably ascertained from the inputs and those which cannot. No language model can tell you the outcome of a fair coin flip. If you want a reasonable test, you can test autoregressive models on out of domain tasks like MNIST classification after pasting raw pixel values into the chat. This is a meaningful test because there’s enough information in the input to determine the outputs (any CS undergrad can train a model to do this). For the cases tested in the article, we can’t tell if there’s just not enough information to make a decision, or if the task is too far out of domain. Given GPT’s performance in other out of domain tasks, it’s likely the issue is both in this case.