Brukbare sitater fra [[Shtetl-Optimized]] verdt å ha i mente når jeg skriver [[Den Andre Kvanterevolusjonen]], samt litt ymse underholdning. [021106](https://scottaaronson.blog/?p=152) - (CS results are) not exactly discoveries about _physics_, but they don’t have the flavor of pure math either. And even if they have some practical implications for computing (which they do), they certainly don’t have the flavor of nitty-gritty software engineering. So what are they then? Maybe it’s helpful to think of them as “**quantitative epistemology**”: discoveries about the capacities of finite beings like ourselves to learn mathematical truths. On this view, the theoretical computer scientist is basically a mathematical logician on a safari to the physical world: someone who tries to understand the universe by asking what sorts of mathematical questions can and can’t be answered within it. Not _whether_ the universe is a computer, but what _kind_ of computer it is! - (...) Indeed, that’s exactly why I chose to work on quantum computing: not because I want to build quantum computers (though I wouldn’t mind that), but because I want to know what a universe that allows quantum computers is _like_. [051005](https://scottaaronson.blog/?p=478) - To be clear, I’m not advocating some sort of woo-woo philosophy of mathematics. I don’t have a philosophy of mathematics — or if I do, then it’s naïve Platonism. All I’m advocating is that we consistently adopt the same standards of convincingness that we already adopt when arguing in front of a blackboard. I leave as an open problem how all of this applies to the “softer” sciences, like biology or string theory. - But until the post-paper world I’m championing becomes a reality, what should you do? Here’s my advice: **write the most informal, sloppy, essayistic, stream-of-consciousness, conversational papers you can possibly get away with. Write as if you were firing off an email to a skeptical but impatient friend.** I promise to do my part by reviewing such papers leniently (at least in terms of the presentation), and no longer demanding pointless revisions. [Guest blog 150104](https://blog.computationalcomplexity.org/2004/01/advice-not-quantum-kind-by-guest.html?m=1) - I think the key is to _start doing creative original research right away_. My first year at Berkeley, I took three courses a semester, hoping to prepare by stuffing my brain with knowledge. This was a mistake. Take as few courses as you can get away with, besides directly relevant ones like complexity theory. Learn what you need to know _while_ doing research, not beforehand. This approach has two advantages. First, you never know what you need to know until you need to know it. Not even Einstein could have predicted as a student that he'd need differential geometry to invent general relativity. And second, you don't _really_ understand anything unless you have a personal stake in it -- meaning that you discovered it, rediscovered it, extended it, applied it, tested it, implemented it, reinterpreted it, explained it to others, etc. This the reason most students forget everything in a course right after the exam. (As Feynman said, "what I cannot create, I do not understand.") - As for me, I like to start with physical or philosophical questions (can we assign any meaning to "the past" besides memories and records in the present? is there a theory that agrees with quantum mechanics on all experiments to date but that wouldn't allow quantum computation? why should we expect information content to be proportional to area rather than volume?), and then look for related questions that can be addressed using complexity theory. But I don't know if anyone else works that way. [181005](https://scottaaronson.blog/?p=15) - My solution is to replace talks by “conversations” whenever possible. Here’s how the Aaronson system works: you get five minutes to tell your audience something unexpected. (Usually this will involve no slides, just a board.) Then, if people have questions, you answer them; if they want details, you provide them. At any time, anyone who’s no longer interested can get up and leave (and maybe come back later), without being considered a jerk. When there are no further questions, you sit down and give someone else a chance to surprise the audience. // If you don’t think this system would work, come visit our quantum algorithms lunch at Waterloo, Tuesdays at 11:30 in the BFG seminar room. Bring a result or open problem. [221005](https://scottaaronson.blog/?p=18) - Most theoretical computer scientists could not blend in among mathematicians. Avi Wigderson, one of the few who can and does, once explained the difference to me as follows. Mathematicians start from dizzyingly general theorems, then generalize them even further. Theoretical computer scientists start from incredibly concrete problems that no one can solve, then find special cases that still no one can solve. [271005](https://scottaaronson.blog/?p=23) ser ut til å implisere at å søke gjennom string landscape for å finne vakum konsekvent med vårt univers er NP-hardt, i hvilket tilfelle både idéen om å bruke maskinlæring og kvantedatamaskiner blir pipe dreams. Men kanskje det går dypere enn som så, og blir et argument mot strengteorien selv: for som Scott skriver, - «If finding an “optimal” Calabi-Yau is so hard, then how did Nature do it in the first place?» - (Med en invokering av [[Extended Church-Turing-Deutsch thesis]] såklart.) - «To me, this raises an interesting question: does science need a notion of “resource-bounded falsifiability,” which is to Popper’s original notion as complexity is to computability?» [051205](https://scottaaronson.blog/?p=35) - As Douglas Adams, another Cambridge alum, put it: “I love deadlines. I like the whooshing sound they make as they fly by.” [201205](https://scottaaronson.blog/?p=40) - _If you’ve never missed a flight, you’re spending too much time in airports._ - (Here,) Umesh was communicating an entire philosophy of life: _concentrate on the high-order bits._ The squash player who runs back and forth to attempt every shot, the student who’s never late with an assignment, the researcher who stalks an unimportant problem like Captain Ahab: all have succumbed to the tyranny of the low-order bit. They need to realize that, as in a randomized algorithm, occasional failures are the inevitable byproduct of a successful strategy. If you always win, then you’re probably doing something wrong. [160723](https://scottaaronson.blog/?p=7409) - We’re now in an era where we’re going to see more and more of this stuff: call it the “pass the popcorn” era of potential quantum speedups for physical simulation problems. And I’m totally fine with it—as long as people communicate about it honestly, as these authors took pains to. - I remember that years ago, probably during one of the interminable debates about D-Wave, Peter Shor mused to me that quantum computers might someday show “practical utility” without “beating” classical computers in any complexity-theoretic sense—if, for example, a single quantum device could easily simulate a thousand different quantum systems, and if the device’s performance on any one of those systems could be matched classically, but only if a team of clever programmers spent a year optimizing for that specific system. I don’t think we’re at that stage yet, and even if we _do_ reach the stage it hopefully won’t last forever. But I acknowledge the possibility that such a stage might exist and that we might be heading for it.