I don't know if this particular design will work but I expect to see a lot more attempts now that the idea has entered the public consciousness.
Current social networks are gamified for virality which implicitly rewards the lack of nuance. So statements that are as short, simple, and wrong as possible will spread faster within the supporters while encouraging flaming from the opposition. This is such an inherent property of every social network in existence that I didn't even realize fixing it was an option.
Unfortunately I got tired of the gimmick pretty quickly and didn't make it to the next few examples. Having to drive a car just to open a link is too much work!
A couple of considerations that come to mind for a database: (a) efficiency, and (b) dynamicity. The tree structure isn't particularly efficient (it has a lot of space overhead, and I think it's also not as fast), so you'd prefer something else if possible. So people often use suffix arrays + LCA preprocessing instead. However, those are hard to make dynamic (your database is constantly changing), so I'd expect that still makes it tough to use them in databases. Though I suspect this isn't the whole story.
Not _quite_ a suffix tree, but a similar structure called a GADDAG is sometimes used in word-generating board games (Scrabble, Words With Friends).
GADDAGs are different because they're more like "reversed prefix" trees, but they help with the issues of placing a new word from a dictionary onto the board using the existing letters of another word.
The answer turns out to be pretty boring: As long as humans are still better than machine, humans can provide algorithmic insights and be a source of cheap labels.
So I am pretty pessimistic about this particular task. There are only a small handful of humans in the world who are qualified to help! (according to IMO scores: https://www.imo-official.org/hall.aspx)
The pool of people who can solve IMO problems is much larger than the pool of people who can solve IMO problems at the rate of one every 90 minutes.
Also consider that fact that human IMO contestants have little training in university-level mathematics. The problem setters try to choose problems where knowledge of advanced mathematics doesn't help, in order to produce a level playing field which only measures raw problem-solving ability. But I suspect that postgraduate-level mathematics will nevertheless be useful in programming the AI.
> Also consider that fact that human IMO contestants have little training in university-level mathematics.
I don't think this is true, as in my experience many of the contestants have already cultured a background in calculus but refrain from using it as the problems are usually designed to actively discourage its use.
This definitely depends on the country. There’s a reasonable amount of calculus in high school (strictly sixth form) mathematics in the U.K. The things one tends to see in university begin with (abstract) algebra and analysis with some “calculus” topics being things like vector calculus, more generic R^n->R^m calculus and contour integration.
I was thinking of mathematics more advanced than calculus, but it provides a good example. The IMO problems are designed to be done without it, but if I was programming a computer to solve IMO style inequality problems I would certainly want it to have the "Lagrange multiplier" method in its toolbox.
People are saying there isn't enough info but I think the author definitely made the right analysis here.
The purpose of partial rollouts is to observe if there are bugs. The unusual case here is that version B's bug is forgetting backward compatibility, causing it to rapidly take down version A too. This means you can't simply rollback B as usual. After you rollback you still need to fix broken A instances. It's a lot of work but it would be the right thing to do.
Instead, they went all in on version B to avoid the bug they just introduced. This is completely reckless. You're skipping your usual process so you never get a chance to observe for other bugs in B. You should actually expect B to have even more bugs in it given you know it already has one major production breaking bug.
Going all in on a version that you're not confident in just to fix the one bug you know about is stupid.
With the info given, it's entirely possible that the bug was actually in version A. Perhaps sending it a payload that is perfectly acceptable by the spec of how the API should work caused A to crash.
In that world, "fixing" B could involve sending invalid or unintended data to work around the problem in A, or patching A before rolling out B (which, when you're at the point of rolling out A.2, you may as well just roll out B)
I don't know if this particular design will work but I expect to see a lot more attempts now that the idea has entered the public consciousness.
Current social networks are gamified for virality which implicitly rewards the lack of nuance. So statements that are as short, simple, and wrong as possible will spread faster within the supporters while encouraging flaming from the opposition. This is such an inherent property of every social network in existence that I didn't even realize fixing it was an option.