Some might say that 2 is as made up as infinity.
Let me elaborate a little - your brain together with society made an abstraction "apple", and only by not distinguishing between these "sets" of atoms you can have numbers.
Well do you say it or are you just playing devils advocate? The post you are responding to seems very straightforward.
If you wanna go all philosophical, “real” might just be anything that is useful. In that way infinity is real because you can use it to do calculus. On the other hand, there are ways of doing calculus that do not involve thinking about infinity. But if you’re gonna count to three apples you pretty much have to go through “two” no matter what.
I was in academia in the pre-GPT-3 era and I don't see a difference between the superficial pass-the-criteria understanding of things then and now. People already rely on a ton of sources, putting their faith into it, recent replication crisis in social sciences had nothing to do with any LLMs.
The problem of academia lies in the first paragraph of this article - supervisor that has to choose doing incremental, clearly feasible stuff. Currently it's called science, but I like to call it knowledge engineering because you're pretty much following a recipe and there is a clear bound on returns to such activities.
Interesting thing: I've got my internal request that is similar to this pelican. And there was 0 progress on it in the past ~2 years. Which might have at least a couple of explanations. 1. Spillage into the pre-training: some real artist had drawn a pelican riding a bicycle. 2. Seeing it as an important discourse for model intelligence in the training data might affect allocation of compute into solving this problem, either thru engineers or the model itself finding the texts about this challenge.
