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Julia has roughly 2 different IRs that live pre LLVM (one for type inference, one for Julia level optimization). This is a proposed replacement to both of these. The reason not to go MLIR is that writing Julia is a lot nicer than writing C++.

median of median does give you guarenteed n*log(n) but it doubles your memory reads per pass making it pretty poor. single random is almost guarenteed to take fewer passes (and median of 3-7 random values can make the number of extra passes over the minimum to be very low)

it's arguably more of a cpu bug than a computer bug. The problem is that predictable data determined whether a cmov or a branch is faster. cmov is only faster than if when the branch is unpredictable. Summer the compiler doesn't know what values your program will be called with, it can only pick and hope. To fix this, cpus could have an instruction like cmov but that learns whether speculation would be profitable and converts to treat it like a branch if better.

the problem with oral societies isn't that they unable to transmit information (in the Shannon sense) it's that they're really bad at transmitting information through time while separating true facts about history from fables, revisionism, bias, she intermixing with pure fiction.

SpaceX started moving into their own constellations because lower prices open up new markets, and this lets them access those markets without having to lower launch prices

the alternate take here is that even at current prices, falcon 9 is more than capable of completely filling space demand which makes building a >10x bigger vehicle seem kind of dumb

it's not just that they have the same asymptomatic. once you do the radix conversion (e.g. base 10 has log(10)/log(2) times more symbols), any 2 definitions are only off from each other by a constant

yeah for real time signals higher frequency makes sense (very briefly before you fft and kill the high frequencies), but for stored signals nyquist is king.

it depends what the purpose of grading is. if the people is to purely assess, grading question by question is better. if the purpose is to provide feedback, knowing how the student did in general can substantially help with identifying what to emphasize

no (in both directions). lots of np/exp problems paralize well and you can be in NC and parallelize really inefficiently (e.g. you can get a 10x speedup, but you need 1000000x the hardware). the better framing is that NC is the class of efficient algorithms that can be sped up near arbitrarily by parallelization

Add/Sub isn't 1 cycle if you want overflow handling. One of the really nice parts about float is that it loses precision gradually.

The us got those agreements in the first place in exchange for 0% tarrifs for international trade. Now that the US has dropped free trade, there's very little incentive for other countries to hold to their side of the deal. If europe wanted to, they could really go to 25 year on US copyright with a plan to go to 0 if there was retaliation

it may be really good pr, but it's really bad for their IPO. If their market for future models is usa only, their potential revenue is cut by 50% at least. (and it's even worse because it means Europe, India, and China will all have companies making their own models that anthropic needs to stay ahead of)