Erdos was an incredibly prolific mathematician, and one of his quirks is that he liked to collect open problems and state new open problems as a challenge to the field. Many of the problems he attached bounties to, from $5 to $10,000.
The problems are a pretty good metric for AI, because the easiest ones at least meet the bar of "a top mathematician didn't know how to solve this off the top of his head" and the hardest ones are major open problems. As AI progresses, we will see it slowly climb the difficulty ladder.
I don't know how Polymarket works. Were people betting against Polymarket, or was Polymarket just making book and someone else is on the other side of the bets.
This term is a bit ambiguous, and there's some nuances that make it different from both sportsbooks and poker.
They don't ever take a nominal cut, their revenue model is in holding USD deposits and making money of interest.
> No, Polymarket is not the house. All trades happen peer-to-peer (p2p).
The documentation is purposefully misleading, but it's true that unlike a sportsbook, they don't take the risk of bets. It's a classic case of a blockchain company exaggerating to what extent they are on the blockchain and to what extent they are centralized and just minimally wrapping the blockchain, like when NFTs were actually a URL to an image.
Trades do NOT happen p2p, polymarket functions as an escrow, payments are sent to polymarket accounts and released by polymarket. Each prediction market does have their own contract, but Polymarket staff rules on each event through off-chain (although they are based on the wording used in the specific event).
New events are solely released by polymarket staff (although users can 'suggest' markets).
I think most questions on polymarket use order books now. But they used to use AMMs (where people bet against polymarket) and their FAQ says some questions still use them
What "tone"? Why is it unreasonable to say these sorts of things about Stack Overflow, or about any community? How is "your questions and answers need to meet our standards to be accepted" any different from "your pull requests need to meet our standards to be accepted"?
It's hard to explain, but immediately clear to enough people that it explains why so many people aren't sad to see SO fall on hard times.
I get that there have to be some rules, but it comes across like you derive some sort of satisfaction in enforcing rules. Successful sites with user moderation start out with a big population of people who will tolerate the rules in order to participate in the goal of the site, but eventually they end up dominated by people who feel that the very act of enforcing rules is an important contribution. All of the talk of "community" comes across as a thinly veiled version of Cartman's "Respect my authority" from South Park.
Man, if this was irl, you'd be punched in the face or ostracized. That's a quick way to assess if your tone is right.
If you don't have a mental capacity to do that (nothing against you, some people are just born that way) — I pity you, but still, try to be 'helpful' over 'correct'. That's how civilization is built.
Wikipedia also have this problem, with moderators using some 'wiki-speak' jargon to 'win the comment battles'.
The Friends of the Wanamaker Organ society is doing work with the new owners towards preservation. I doubt it's going anywhere, but concerts will be sporadic for a while.
It's not that obscure, even in the US. Anyone who takes French in US high school has probably read it in French (it's very easy to read), and even in English it's one of the most common classic children's books.
Angband is a roguelike that had many variants over the years, and Nick combined all of these variants into one big git repository where each variant is a branch.
I found the claim that Peirce rejected bivalent logic strange, simply because he was one of the key figures in actually creating bivalent logic, in his paper "On the Algebra of Logic". He even proposed one of the classic forms of the law of excluded middle known as Peirce's law.
The problems are a pretty good metric for AI, because the easiest ones at least meet the bar of "a top mathematician didn't know how to solve this off the top of his head" and the hardest ones are major open problems. As AI progresses, we will see it slowly climb the difficulty ladder.
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