
Fewer than 10k people have the skills necessary for AI research? - byzgen
This seems low. Are there fewer than 10k people with a master&#x27;s in the subject in the entire world? How do you think they calculated it?<p>&quot;Solving tough A.I. problems is not like building the flavor-of-the-month smartphone app. In the entire world, fewer than 10,000 people have the skills necessary to tackle serious artificial intelligence research, according to Element AI, an independent lab in Montreal.&quot; https:&#x2F;&#x2F;www.nytimes.com&#x2F;2017&#x2F;10&#x2F;22&#x2F;technology&#x2F;artificial-intelligence-experts-salaries.html?
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indescions_2017
Exploding demand is the real catalyst producing AI talent shortages. At both
the Fortune 100 end of the spectrum, as well as the 3-person garage startup
level.

Think about Spotify's Discover Weekly feature and how it multiplies user
engagement. Collaborative filtering of 100M users can possibly be done by a CS
undergrad on their NVidia 1050 gaming laptop in a couple of hours. Metadata
analysis of 1B songs is more of a grad level problem for someone with access
to the departmental research cluster. But machine learning audio tempo,
frequency and pitch similarity for thousands of new songs added daily? That
requires a corporate R&D budget and dedicated cloud GPU resources. And at
least one luminary for the "breakthrough" that takes you from 95% to 97-99%
human level understand which will make the technology world competitive.

The great thing about AI that perhaps many overlook is that genius is not
required to build a startup with unicorn status valuation ;) Look at the
recent YC article on Toutiao, where a handlful of engineers built a news
content generation algorithm in a few months. If your input data quality is
very high at the outset, even standard sci-kit out of the box t-SNE
classification can prove "unreasonably effective"!

The Hidden Forces Behind Toutiao: China’s Content King

[http://blog.ycombinator.com/the-hidden-forces-behind-
toutiao...](http://blog.ycombinator.com/the-hidden-forces-behind-toutiao-
chinas-content-king/)

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codeonfire
Of the 5-10k CS professors out there , only a fraction are researching AI.
There are postdocs, grad students, undergrad researchers. Students are not
likely to make any ground breaking discoveries. So yeah, under 10k sounds
reasonable. CS is not as big as some people think. There have been less than
50k CS pHd's conferred in all human history and less than 500k master degrees.

With AI though, the jobs probably pay $300-500k per year, so there are going
to be a lot of people flat out lying about credentials and abilities.

And some people's idea of "research" is running scripts against Azure, AWS, or
some grad student's thesis code. "Research" most likely does not involve a
large amount of computing.

~~~
somethingsimple
> There have been less than 50k CS pHd's conferred in all human history and
> less than 500k master degrees.

Do you have a source for those figures?

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codeonfire
[https://nces.ed.gov/programs/digest/d16/tables/dt16_324.10.a...](https://nces.ed.gov/programs/digest/d16/tables/dt16_324.10.asp?current=yes)
[https://nces.ed.gov/programs/digest/d16/tables/dt16_323.10.a...](https://nces.ed.gov/programs/digest/d16/tables/dt16_323.10.asp?current=yes)

This is US only and not for all years.

~~~
somethingsimple
Thanks!

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dagw
All depends on how you define "tough A.I. problems". Basically for all N>0
there exists a definition of "tough" such that less than N people are capable
of "Solving tough A.I. problems"

For any reasonable definition, just having a Masters in a subject certainly
does not qualify you to do tough AI research. For that matter just having a
PhD in a subject doesn't really qualify you to do high quality research in
that subject.

That being said there is a lot of 'easy' AI problems out there to be tackled.
Take just about any random domain that you even a basic understanding of,
collect some data, apply some interesting sounding algorithms from scikit-
learn to that data, tweak some parameters, does anything interesting fall out?
If no try some new data and/or new algorithms. Repeat until something
interesting happens. Congratulations you've just done some AI research,
probably good enough to be published somewhere, and all you needed was high
school level math and some basic programming skills.

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csa
Frankly, I think that there are fewer than 10k people who have the skills for
_quality_ research in pretty much any field (n.b., the all-too-frequent
p-hacking researcher is not "quality").

I don't think that this is news.

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pvaldes
Having skills is not enough. Is more a question of having enough resources,
and interesting questions crossing the road in your way.

And (fortunately) many great discoveries are a question of pure luck. I wonder
how this fits in their model.

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mockingbirdz
Judging just by the number of people doing the CS231n course online
[http://cs231n.stanford.edu/](http://cs231n.stanford.edu/), the number of
would-be practitioners who have the skills is definitely increasing. CS231n is
a graduate level class and is conceptually harder than a "flavour of the
month" app. Add to that the number of articles being published on DIY
experiments with AI, I think the 10K number seems small. Do these qualify as
"serious" research? Maybe not, but they are not all trivial.

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mindcrime
Ya know, part of me wants to say "what a load of bollocks. Doing AI research
doesn't take that much that's special." And in truth, it _doesn 't_ take a lot
of what most of us would consider "special". I mean, if you can get through
multi-variable caculus, linear algebra and probability / stats, you pretty
much have the mathematical tools you need. So in that regard, I do think it's
bollocks.

But...

I would argue that AI research (depending on how you define that. AI is a BIG
field) _is_ more demanding that "flavour of the month smartphone app"
development. And in the past, I scoffed when I heard people say things like
"70% of so-called developers can't complete FizzBuzz." Then I started
interviewing a lot of candidates for developer roles at the $dayjob and
whaddaya know... it seems that most of the candidates we get _can 't_
successfully code FizzBuzz. And that's a pretty low bar.

So I dunno... part of me believes there are plenty of people who could
contribute to AI research, but part of me is shocked by how few people can
even write the most trivial computer program.

 _Are there fewer than 10k people with a master 's in the subject in the
entire world?_

I don't think having a Masters has much to do with anything. We get folks all
the time with a Masters in C.S., even from relatively prestigious schools, and
they can't even code up FizzBuzz.

Anyway, I wish I had a better answer for you, but recent experiences have me
questioning just how many really competent people there are out there.

~~~
byzgen
I definitely agree that it's a lot more demanding than smartphone apps - or
most of the rest of what we call software development.

I'm trying to make the switch from backend development to machine learning
right now, and even though I have a supportive employer I've begun thinking
about going back to school because the math involved seems steeper and harder
to avoid.

Disclaimer: My math level is high school since I self-taught my way into
software engineering.

~~~
mindhash
What are the concepts you are most struggling with..could you list out a
few..check out metacademy.org

~~~
byzgen
I never took statistics or linear algebra. Only AP calculus. So when people
refer me to academic papers (or even Wikipedia most of the time) I'm not able
to understand it.

I can study on my own, and have been for stats/probability. But started asking
myself, why not just get a degree and make it quicker. I'd have to leave my
job for a number of years, but then I'd be able to study all day instead of
nights/weekends.

~~~
graphene
There's deeplearningbook.org, which starts with the basic maths and then goes
into considerable detail on cutting edge work.

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myaso
It assumes a math background implicitly. I feel like you need some context
already to get value out of it. I wouldn't bother reading it without doing
something hands on or going through another course like cs231n or fastai
first. It's an excellent book regardless of the above points.

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PaulHoule
I think the skills to develop training sets and develop real applications are
even rarer.

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jventura
Well, where I took my PhD degree (I'm not in the US), I was the only one
working on Text-mining and Information Retrieval (besides my professor), and I
think there was only three or four other PhD students working on AI - one on
SOM (Self-Organizing maps), one on automatic translation, and the others I
can't recall exactly on what they were working on.

So, although 10K seems too few to me, I would say that the magnitude may be
right..

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p1esk
One way to estimate: how many people have published in top conferences (CVPR,
ICML, NIPS, etc) as a first author?

Those are the people who can do serious AI research.

