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This is a chicken and egg problem that I believe exists in Computer Engineering/developer positions because of i) the extremely diverse background of hires (som

This is a chicken and egg problem that I believe exists in Computer Engineering/developer positions because of i) the extremely diverse background of hires (some of them not being engineers or mathematicians or physicists per se i.e. could be coming in with a bio background (ML usually), no degree at all (perhaps a bootcamp -- usually front end work), or other) ii) a lot of businesses do low hanging fruit work with little novelty, iii) a lot of cost can be thrown to "buy more hardware/server time," iv) low quality is not just advised but sought for. Because of the usual lack of rigorousness -- e.g. most companies will not require you to prove that the system is going to be up for 99.9999% of the time, the load balancing is optimal, the abstract queue in our system is not going to diverge (when it does inevitably we will just reboot and keep doing it until we get more funding) -- the expectation and targets is also to avoid it. Most developer positions are doing essentially the equivalent of designing over and over the equivalent in civil engineering terms of one or two story buildings. There are positions that will exercise one's engineering skills (including math). However, the culture and expectation of "math person" does not promote them. Graphics, cryptography, distributed/byzantine systems (I don't mean using AWS here), optimization, ML (new algorithms/improvements), maps, are some areas that one's cs/math/engineering skills can be used at. But note that when any X of those areas become trendy there is the gut reaction of an "intro to X for programmers" coming out that is a couple of hand-wavy sketches, some sketchy intuition -- most often wrong in the details -- and an API guide. Having done my undergraduate in Europe, every year was math heavy -- math was the core not the attrition machine. And I do see this mentality in the U.S. startup industry where a lot of times the Edison approach is taken of trying every single filament width choice on a mock-up instead of doing a quick calculation. Having taught math to undegrads in the U.S. and from discussions with people that TA'd, I would agree with you that the math curriculum needs to be revised from the ground up as being extremely inadequate. On the other hand, most software "engineer" positions, do not require any engineering to be done.

hnfong 5y ago
I don't believe it is a chicken and egg problem. I believe there aren't that much of a demand in the industry for solving "Math" problems. From an (software even!) engineering perspective, nobody needs to solve the same Math problem twice. All "Math problems" are either solved or are open problems (this is almost by definition). The ones which are already solved do not require re-solving again, which means that in the vast majority of cases a competent (software) engineer only needs to learn how to apply them. I don't know about traditional engineering, but in software, often it's just a matter of importing a library and calling an API. The software development ecosystem has developed to a point where you don't need to know how to implement things, you just need to know what you need. Unless you're an expert specialist in a particular field, you often can't do better than that, because whatever idea you have, most likely somebody more competent than you has already written an open source library for that. I don't think it's useful to contrast general incompetence with a lack of mathematical ability -- though it sometimes correlate somewhat if only because general intelligence often manifests in mathematical ability. There are simply too many unproven assumptions from "math education" => "writing better software". If anything, good software engineers need to be ready to learn, and learning maths outside of formal schooling is just one of the many things they need to do. The general lack of quality in software is a supply and demand problem -- as long as FAANG can afford to pay 200k+ USD to fresh grads with no experience, companies with a smaller budget must make a trade off between lowering quality and not delivering at all. Ironically(?) the market is actually responding. People doing interview prep are learning the minimum subset of mathematics and engineering required for a high paying software job. Then you get people complain about grinding leetcode. Imagine what happens if FAANG companies add abstract set theory to their standard interview questions! (I'm willing to bet this would lower software quality...)

hnfong 5y ago

I don't believe it is a chicken and egg problem. I believe there aren't that much of a demand in the industry for solving "Math" problems. From an (software even!) engineering perspective, nobody needs to solve the same Math problem twice. All "Math problems" are either solved or are open problems (this is almost by definition). The ones which are already solved do not require re-solving again, which means that in the vast majority of cases a competent (software) engineer only needs to learn how to apply them. I don't know about traditional engineering, but in software, often it's just a matter of importing a library and calling an API. The software development ecosystem has developed to a point where you don't need to know how to implement things, you just need to know what you need. Unless you're an expert specialist in a particular field, you often can't do better than that, because whatever idea you have, most likely somebody more competent than you has already written an open source library for that. I don't think it's useful to contrast general incompetence with a lack of mathematical ability -- though it sometimes correlate somewhat if only because general intelligence often manifests in mathematical ability. There are simply too many unproven assumptions from "math education" => "writing better software". If anything, good software engineers need to be ready to learn, and learning maths outside of formal schooling is just one of the many things they need to do. The general lack of quality in software is a supply and demand problem -- as long as FAANG can afford to pay 200k+ USD to fresh grads with no experience, companies with a smaller budget must make a trade off between lowering quality and not delivering at all. Ironically(?) the market is actually responding. People doing interview prep are learning the minimum subset of mathematics and engineering required for a high paying software job. Then you get people complain about grinding leetcode. Imagine what happens if FAANG companies add abstract set theory to their standard interview questions! (I'm willing to bet this would lower software quality...)