Jagged AGI: o3, Gemini 2.5, and everything after

In the last example (the riddle)--I generally assume the AI isn't misreading, rather that it assumes you couldn't give it the riddle correctly, but it has seen it already.

I would do the same thing, I think. It's too well-known.

The variation doesn't read like a riddle at all, so it's confusing even to me as a human. I can't find the riddle part. Maybe the AI is confused, too. I think it makes an okay assumption.

I guess it would be nice if the AI asked a follow up question like "are you sure you wrote down the riddle correctly?", and I think it could if instructed to, but right now they don't generally do that on their own.

> generally assume the AI isn't misreading, rather that it assumes you couldn't give it the riddle correctly, but it has seen it already.

LLMs doesn't assume, its a text completer. It sees something that looks almost like a well known problem and it will complete with that well known problem, its a problem specific to being a text completer that is hard to get around.

Text Completion is just the objective function. It's not descriptive and says nothing about how the models complete text. Why people hang on this word, I'll never understand. When you wrote your comment, you were completing text.

The problem you've just described is a problem with humans as well. LLMs are assuming all the time. Maybe you would like to call it another word, but it is happening.

With a plan, aiming for something, that's the difference.

So do LLMs. "In the United States, someone whose job is to go to space is called ____" it will say "an" not because that's the most likely next word, but because it's "aiming" (to use your terminology) for "astronaut" in the future.