6 ms·

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

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.

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.