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I am amazed that rather than see this as opportunity for racking up top $$$ for at least the next 3-10 years by learning Calculus, Probability/Statistics, and L

I am amazed that rather than see this as opportunity for racking up top $$$ for at least the next 3-10 years by learning Calculus, Probability/Statistics, and Linear Algebra on the way to whatever degree one seeks, there is so much criticism of this. This situation is a pure win for smart people who put their minds to the task at hand. Buzzwordy or not, AI/ML/Newfangled Regression has more than enough wins with speech recognition, game-playing, image recognition, and recommendations to have a strong future. Or, if you insist on negativity and you prefer to expend your time kvetching about whether Famous CS Person X or Famous CS Person Y should make the most money (Fantasy Data Science?), then more for me getting $h!+ done whilst you bicker. I mean I scratch my head that Mark Wahlberg is the highest paid actor in Hollywood, but hey, good for him in my book. Too bad his burger shop is crap.

paultopia 9y ago
Is the first paragraph of this actually true though? At least if you believe the article, the people racking up those salaries are CS/ML/Stats phds, not people who learned stats and linear algebra on the way to their biochem degree or sociology degree or maybe even EE degree. It seems like the idea is more people who can produce truly novel work. Moreover, the article also claims there's a pipeline for the folks (below the PhD level? The writing is a little unclear) that's coming out: " At the current education rate, an influx of new experts will start to moderate salaries in three to four years, he says." So who is it who is making educational choices today who will be well-positioned to cash in. Probably nobody. Rather, like with all talent shortages, the people who win are those who had the luck or foresight to have already studied something that happened to get big, and now everyone else is rushing to catch up and flood the market.
- electricslpnsld 9y ago
  > Is the first paragraph of this actually true though? I know quite a few folks at Apple and Google without PhDs in machine learning who are now making damn good money working on ML in more research oriented capacities.
  - noobhacker 9y ago
    Could you say a bit about their background? (e.g. degree type, work experience, self-education) Given that a lot of this thread is about how one can make it in this field without a PhD in ML, your comment would be very illuminating.
    - electricslpnsld 9y ago
      One is a former game developer (with only a high school degree) who happened to have an interest in ML and studied up in his free time. A few were in a startup, bachelors in Computer Science from non-Stanford universities, that was doing AI work and was acquired. Another is a developer of a prominent open source package, originally utterly unrelated to AI, but he started working on learning related applications with his software and landed at Google as a result. Another is a friend with a PhD but in a totally different area (Computer Graphics) who was hired into Google where she landed on a ML team.
    - deleted 9y ago
      [deleted]
- cjalmeida 9y ago
  If even a fraction of AI promises come to fruition, there'll be a huge demand for AI implementers in varied fields. Thing is general AI, as developed by Google et al is usually only a starting point. There's a lot of engineering effort required to make a valuable solution out of it.
- varelse 9y ago
  My doctorate is not in CS, Math or an engineering field, but I did (somewhat unknowingly) apply ML/statistics to my thesis, which was (more or less) generative adversarial search 20+ years ago. Everything I did then turned out to be strongly related to techniques like Naive Bayes, Logistic Regression, Principal Component Analysis, Boosting, Bagging, and bunch of other techniques that get reinvented over and over again. Once I mapped them over to their ML incarnations, they were familiar territory going forward.
bilbo0s 9y ago
I agree with your position vis-a-vis all of the complaining that people seem to be engaged in here. That said, I think it's a bit unfair to imply that the only thing required of people to participate in this particular frenzy would be to learn a little probability and statistics. I've been working on a system that learns from an enormous set of medical imaging studies for the purposes of analyzing same, and the technical ML and domain knowledge you need to bring to that party is actually pretty humbling. You're not gonna do this stuff with a little statistics and some H1B's. At least, not in a fashion that any medical practitioner will take seriously. I think in a few years, you'll have lots of lower level people who will know enough to provide meaningful contributions. Of course, the flip side of that is that their salaries will be significantly lower.
adventured 9y ago
> I mean I scratch my head that Mark Wahlberg is the highest paid actor in Hollywood Alternatively Dwayne Johnson as well (whom I happen to enjoy more than Wahlberg). He doesn't do high-brow entertainment (starting from his wrestling days). Simple, fun entertainment for a super broad audience never goes out of style. Your average person is pretty happy to forget their 9to5 and troubles, and go see a big movie for escapism. That will never cease to be true. Arnold Schwarzenegger filled that role when I was a kid. That's not a criticism at all, it serves just as legitimate of a purpose as people that prefer to watch TED Talks instead of the next Rock action flick. My father had a basic saying that I didn't appreciate until I was much older; whenever I would criticize something that seemed a bit neanderthal-like (so to speak), he'd respond with: it takes all types. Generically what he meant, was that the world functions courtesy of a wild variety of all types of people. Would it function better if everyone were elitist and brilliant? I don't think so. Miranda Sings, Jenna Marbles, PewDiePie, minecraft videos, twitch game streaming, et al., same fundamental as Wahlberg and The Rock.
- deleted 9y ago
  [deleted]
joshuamorton 9y ago
I think you're misunderstanding who these high salaries are for. It's not for people who brushed up on their sophomore math courses. The demand is for people with graduate degrees and postgraduate experience with published papers and a pedigree that leads one to expect continued novel work at the level of cutting edge research.
wufufufu 9y ago
I suspect that calculus, statistics, and linear algebra are required for most 4-year CS degrees. Some schools even have an "AI" track for their undergrad degrees. This article specifically refers to PhDs in Machine Learning, which is much higher bar. If you do research in the same area that Google's research department is throughout your graduate degree, net research internships at insert fancy company with AI component here every summer, and get a PhD, $300k seems completely reasonable. Personally, I think we're in a SaaS bubble and an AI bubble. "AI" isn't nearly as developed or useful as the amount of VC money being dumped into it.
- cryptoz 9y ago
  > "AI" isn't nearly as developed or useful as the amount of VC money being dumped into it. That's the entire point of VC though - VCs don't put money into regular roads or into normal houses, as these things have already got their usefulness determined and we know they're darn useful. VCs pump money into things that look like they could use a few billion dollars to get developed and ready for the mass market. AI fits that perfectly according to your description. VCs who put money into things that are already proven are VCs who are missing out on the Next Big Things. "AI" will become fully developed largely using the money that VC is putting into it.
  - aje403 9y ago
    Completely agree. These are intelligent people who have done their research and are now making an informed bet. Whether or not their investment was justified remains to be seen.
  - wufufufu 9y ago
    Good point. My issue is that when I hear that a startup is AI-focused, that means they're just implementing something with machine learning (and possibly unnecessarily). These startups generate a lot of hype, which I believe is unwarranted. I imagine Google researchers are working towards advancing AI techniques and knowledge more generally, not trying to disrupt some industry with existing machine learning techniques.
- 9y ago
godelmachine 9y ago
Truer words have never been spoken

paultopia 9y ago

Is the first paragraph of this actually true though? At least if you believe the article, the people racking up those salaries are CS/ML/Stats phds, not people who learned stats and linear algebra on the way to their biochem degree or sociology degree or maybe even EE degree. It seems like the idea is more people who can produce truly novel work. Moreover, the article also claims there's a pipeline for the folks (below the PhD level? The writing is a little unclear) that's coming out: " At the current education rate, an influx of new experts will start to moderate salaries in three to four years, he says." So who is it who is making educational choices today who will be well-positioned to cash in. Probably nobody. Rather, like with all talent shortages, the people who win are those who had the luck or foresight to have already studied something that happened to get big, and now everyone else is rushing to catch up and flood the market.

electricslpnsld 9y ago
> Is the first paragraph of this actually true though? I know quite a few folks at Apple and Google without PhDs in machine learning who are now making damn good money working on ML in more research oriented capacities.
- noobhacker 9y ago
  Could you say a bit about their background? (e.g. degree type, work experience, self-education) Given that a lot of this thread is about how one can make it in this field without a PhD in ML, your comment would be very illuminating.
  - electricslpnsld 9y ago
    One is a former game developer (with only a high school degree) who happened to have an interest in ML and studied up in his free time. A few were in a startup, bachelors in Computer Science from non-Stanford universities, that was doing AI work and was acquired. Another is a developer of a prominent open source package, originally utterly unrelated to AI, but he started working on learning related applications with his software and landed at Google as a result. Another is a friend with a PhD but in a totally different area (Computer Graphics) who was hired into Google where she landed on a ML team.
  - deleted 9y ago
    [deleted]
cjalmeida 9y ago
If even a fraction of AI promises come to fruition, there'll be a huge demand for AI implementers in varied fields. Thing is general AI, as developed by Google et al is usually only a starting point. There's a lot of engineering effort required to make a valuable solution out of it.
varelse 9y ago
My doctorate is not in CS, Math or an engineering field, but I did (somewhat unknowingly) apply ML/statistics to my thesis, which was (more or less) generative adversarial search 20+ years ago. Everything I did then turned out to be strongly related to techniques like Naive Bayes, Logistic Regression, Principal Component Analysis, Boosting, Bagging, and bunch of other techniques that get reinvented over and over again. Once I mapped them over to their ML incarnations, they were familiar territory going forward.

bilbo0s 9y ago

I agree with your position vis-a-vis all of the complaining that people seem to be engaged in here. That said, I think it's a bit unfair to imply that the only thing required of people to participate in this particular frenzy would be to learn a little probability and statistics. I've been working on a system that learns from an enormous set of medical imaging studies for the purposes of analyzing same, and the technical ML and domain knowledge you need to bring to that party is actually pretty humbling. You're not gonna do this stuff with a little statistics and some H1B's. At least, not in a fashion that any medical practitioner will take seriously. I think in a few years, you'll have lots of lower level people who will know enough to provide meaningful contributions. Of course, the flip side of that is that their salaries will be significantly lower.

adventured 9y ago

> I mean I scratch my head that Mark Wahlberg is the highest paid actor in Hollywood Alternatively Dwayne Johnson as well (whom I happen to enjoy more than Wahlberg). He doesn't do high-brow entertainment (starting from his wrestling days). Simple, fun entertainment for a super broad audience never goes out of style. Your average person is pretty happy to forget their 9to5 and troubles, and go see a big movie for escapism. That will never cease to be true. Arnold Schwarzenegger filled that role when I was a kid. That's not a criticism at all, it serves just as legitimate of a purpose as people that prefer to watch TED Talks instead of the next Rock action flick. My father had a basic saying that I didn't appreciate until I was much older; whenever I would criticize something that seemed a bit neanderthal-like (so to speak), he'd respond with: it takes all types. Generically what he meant, was that the world functions courtesy of a wild variety of all types of people. Would it function better if everyone were elitist and brilliant? I don't think so. Miranda Sings, Jenna Marbles, PewDiePie, minecraft videos, twitch game streaming, et al., same fundamental as Wahlberg and The Rock.

deleted 9y ago
[deleted]

joshuamorton 9y ago

I think you're misunderstanding who these high salaries are for. It's not for people who brushed up on their sophomore math courses. The demand is for people with graduate degrees and postgraduate experience with published papers and a pedigree that leads one to expect continued novel work at the level of cutting edge research.

wufufufu 9y ago

I suspect that calculus, statistics, and linear algebra are required for most 4-year CS degrees. Some schools even have an "AI" track for their undergrad degrees. This article specifically refers to PhDs in Machine Learning, which is much higher bar. If you do research in the same area that Google's research department is throughout your graduate degree, net research internships at insert fancy company with AI component here every summer, and get a PhD, $300k seems completely reasonable. Personally, I think we're in a SaaS bubble and an AI bubble. "AI" isn't nearly as developed or useful as the amount of VC money being dumped into it.

cryptoz 9y ago
> "AI" isn't nearly as developed or useful as the amount of VC money being dumped into it. That's the entire point of VC though - VCs don't put money into regular roads or into normal houses, as these things have already got their usefulness determined and we know they're darn useful. VCs pump money into things that look like they could use a few billion dollars to get developed and ready for the mass market. AI fits that perfectly according to your description. VCs who put money into things that are already proven are VCs who are missing out on the Next Big Things. "AI" will become fully developed largely using the money that VC is putting into it.
- aje403 9y ago
  Completely agree. These are intelligent people who have done their research and are now making an informed bet. Whether or not their investment was justified remains to be seen.
- wufufufu 9y ago
  Good point. My issue is that when I hear that a startup is AI-focused, that means they're just implementing something with machine learning (and possibly unnecessarily). These startups generate a lot of hype, which I believe is unwarranted. I imagine Google researchers are working towards advancing AI techniques and knowledge more generally, not trying to disrupt some industry with existing machine learning techniques.
9y ago

godelmachine 9y ago

Truer words have never been spoken