No, first of all due to imperfections in the manufacture of real coins, there are actually no fair coins.
Also the bias in the probability affects the first throw as well as all the rest. If your dataset is composed of first throws/rest of the throws, you’re going to see they are correlated.
This is probably just because the coins aren’t actually fair. If the coin is slightly biased towards heads, the first throw is more likely to heads, and so are all subsequent throws. Same for tails.
I was pretty intrigued by Aphantasia a while ago, as I can’t picture anything at all with my eyes closed. Then I asked all my friends and none of them could either, apparently. So I’m wondering what “picturing” means in the definition of aphantasia?
With my eyes closed all I see is pitch black, but I can “imagine” myself seeing a red apple even with my eyes open, I don’t actually see anything though.
I think art is much easier for LLM-style AI models to do compared to writing.
To make a nice picture you just need to place pixels near each other in a way that looks good, and we all know LLMs are phenomenal at this.
Good text on the other hand is not just text that has a good flow and fits the prompt. It must follow a line of thought, and LLMs don’t do that by design, even though we could argue wether they have that capability as an emergent one, but I don't believe that at all.
Someone on twitter pointed out that their dating methodology is faulty. Carbon dating makes sense only if used on organic materials in human context. For example, dating charred remains in a hearth with human artifacts in its vicinity.
It seems like the authors in the paper just took a sample from the ground and dated the organic material in it, which doesn’t make much sense.
I can’t find the original tweet atm but I hope I’ve been clear enough.