
'We can't compete': why universities are losing their best AI scientists - sasvari
https://www.theguardian.com/science/2017/nov/01/cant-compete-universities-losing-best-ai-scientists
======
notyourday
Let me see if I can summarize the response:

HTTP/1.1 402 F_YOU. PAY_ME.

Very few things grind my gears more than academic fat cats whining about
losing their slaves to those who make slaves lives better.

Schools want to retain talent? Pay it more money. It is that simple. Can't
afford it? Maybe you should spend less money on salaries of professors ( who
need those slaves to actually do the work ), administrators, fancy buildings,
marketing, sports programs, etc.

None of the professors would take 4/5s pay cut and stay, why should those who
do the work? Everything else is secondary.

~~~
sevensor
As a former grad student, I strogly sympathize with the urge to get the hell
out of there and make real money. But on the flip side, I'm pretty dubious
about the idea of abandoning your program just because the grass is greener in
industry. The Ph.D. improves your chances of getting to work on interesting
problems down the road, even if you leave academia. Selling that out for a few
years of big money isn't something that should be done lightly. Especially
when we're in the middle of such an obvious bubble -- what's the plan for 2-5
years from now when it pops?

~~~
olegkikin
So your argument is they should stay and work for pennies, hoping to get an
"interesting" job in the future, instead of getting an interesting and highly
paid job right now?

It's also not obvious at all it's a bubble. AI field is already much more
complex than the regular CS field, which already suffers from talent
shortages. AI is the future, and the demand is here to stay.

~~~
sevensor
> It's also not obvious at all it's a bubble

It's _breathtakingly_ obvious:

1\. Large numbers of people getting poached from academic programs by
industry.

2\. "This time it's different" is what we've said during every bubble ever.

3\. Lots of money chasing a few ideas.

The only thing that's not clear about this bubble is when it's going to pop.
People who didn't see the potential of the internet in 1996 missed out. People
who got into it in 2000 were left holding the bag.

~~~
notyourday
I think you are missing the scale mentioned in the article:

The industry is paying _five times_ what universities are paying. Not Fifty
percent. Not double. Five times.

Professors/administrators whining about it are pure scum unless they
themselves are making one fifth what they would be making in a different
university that offered them a job purely because they love this specific
college doing the specific research or teaching.

What is really pissing off these professors is that with their worker bees
gone they themselves would need to do the work - something they are not quite
used to.

~~~
sevensor
> I think you are missing the scale mentioned in the article:

> The industry is paying five times what universities are paying. Not Fifty
> percent. Not double. Five times.

Nope, not missing that. You don't think this happened in 1999-2000?

I agree with you that grad students are ruthlessly exploited. I've seen that
firsthand. I routinely discourage people from doing a Ph.D. for that reason.
And if you're not too far along, taking a terminal master's and leaving for
industry is a solid option, especially because this AI bubble won't last
forever. But if, like the one student in TFA, you have just one year left,
quitting grad school is not a great idea. Now you have, at best, an awkwardly
long stretch of grad school on your CV with a master's degree on the end of
it, and at worst, no degree at all to show for your pains. At that point, just
suck it up and finish the degree.

~~~
notyourday
> Nope, not missing that. You don't think this happened in 1999-2000?

I do. I'm yet to see people who jumped away from academic CS tracks at the
time being upset about their decisions. I do know of dozens degreed people in
their late thirties reporting to C students while making quarter of the salary
of the same C students.

~~~
YeGoblynQueenne
CS and AI are different subjects. As a CS dropout, your job is to write code.
You can get quite competent at that without a higher education course.

You can't do that with AI. The amount of material you need to get on top of is
really something else, especially if you want to be able to understand the
foundations of what you're doing- which stretch back several decades before
statistical machine learning, popular as it is today.

~~~
notyourday
It is very naive to think that AI programs in most of universities is anything
other than writing code and pretty lousy one.

Do you know that it was possible to get a PhD in genetic sequencing not a very
long time ago from very serious schools? That's right, what today can be done
by a random student or a random outsourcing shop in a third world country used
to be a PhD worthy specialty.

In 5 years today's ML/AI PhDs would be in the same peculiar position as PhDs
of genetic sequencing.

~~~
YeGoblynQueenne
>> It is very naive to think that AI programs in most of universities is
anything other than writing code and pretty lousy one.

Are you speaking from experience? Because my own experience from my degree and
Master's AI courses and lectures is completely different to what you describe.
Particularly during my Master's, code was only incidental; the meat and
potatoes of each and every lecture was theory.

It depends of course on the quality of the teaching in a given institution,
but, for instance, you can find here the lecture notes from Oxford's Deep NLP
course:

[https://github.com/oxford-cs-
deepnlp-2017/lectures](https://github.com/oxford-cs-deepnlp-2017/lectures)

As you will see, it's anything but just code, or lousy such. Of course, that's
Oxford, their teaching is world-class- but most AI courses I've found on the
internet are similar in scope.

Really, it's pointless trying to teach AI with "just code" \- because in AI
you can't really code much, unless you understand the theory.

>> In 5 years today's ML/AI PhDs would be in the same peculiar position as
PhDs of genetic sequencing.

I think what you're saying is that in 5 years, people knowing Tensor Flow or
Torch will be a dime a dozen.

Perhaps- but someone will still need to figure out some way to acquire new
knowledge.

Also, it bears repeating that AI is not just statistical machine learning and
statistical machine learning itself is not just deep learning. AI is a broad
field with communities focused on many different subjects. Just as an example
you can find information on, easily, try probabilistic programming.

------
CJefferson
Speaking as an AI researcher (although I don't spend all my time in the
current trendy bits), the problem is it seems at the moment what you need to
do successful machine learning is:

* Lots of data

* Lots of CPU/GPU power

That's two places where Universities just can't compete with the money which
companies can throw at this problem. Also, all AI companies have no interest
in working with academia, just taking the staff/students, so there is no
useful 2-way communication.

EDIT: I just wanted to expand one small point. The data and CPU/GPU power seem
to let you research and solve fundamentally different problems. Consider a
classic AI technique, like SAT. If you have lots of computers, you can solve
bigger SAT problems, but there didn't seem to be an interesting research which
required massive clusters of machines, or massive datasets. The big research
improvements were all possible on a single reasonable desktop machine, and a
selection of commonly available benchmarks.

~~~
_delirium
The CPU/GPU power isn't really out of reach of academic budgets anymore. There
are _some_ kinds of problems that are, but AlphaGoZero ran on a box with 4
GPUs, for example, and there is a lot of cutting-edge research with similar
computing budgets. It's more DIY though. You have to spec out and buy your
hardware, maintain it, etc. (or a grad student does that in their "spare
time"), while if you work in AI at Google all the hardware and networking and
such is in most cases left to professionals.

~~~
netheril96
AlphaGoZero runs on 4 TPUs not GPUs. And that is only for inference, not for
training. For training it uses 64 GPUs.

More importantly, AlphaGoZero is the final evolution. To reach this stage one
needs to experiment a lot, and most of the experiments are failures. To do any
meaningful research requires a budget of several times or dozens of times the
amount of computing power, and this is only for one project.

The computation resources at universities are definitely not sufficient.

------
LeifCarrotson
> He had left for a six-figure salary at Apple.

> “He was offered such a huge amount of money that he simply stopped
> everything and left,” said Maja Pantic, professor of affective and
> behavioural computing at Imperial. “It’s five times the salary I can offer.
> It’s unbelievable. We cannot compete.”

Glassdoor suggests that a salary for a machine learning or natural language
processing engineer at Apple averages about $125k. It's not like "6 figures"
means $999,999. ...And this was five times the salary that the professor could
offer, implying the grad student was valued at $25,000 a year. Here are
Imperial's salary guidelines [1]. Given that the student was one year prior to
their PhD, it appears they were capped at £35,850, which is closer to $47k, so
maybe Apple paid $250k, but $47k is still not as much as the person is
obviously worth.

And then she advocates pay caps.

The reason that private industry is willing to pay these people so much is not
some nefarious desire to monopolize the skills and outputs. It's because their
work is able to generate value in excess of that salary.

Universities need to offer professors and grad students a job with a value -
salaries, benefits, and investment in their future - that makes it worthwhile
for them to work there. They've been able to mistreat altruistically minded
students who don't know what they're worth, and allow shortfalls in their
education so they lack the skills to function effectively in the workplace,
but while that may work in some sectors AI scientists are currently so
valuable that it's not using. Let's fix the universities, not place blame on
the companies who are hiring the scientists out of those universities.

[1] [http://www.imperial.ac.uk/media/imperial-
college/administrat...](http://www.imperial.ac.uk/media/imperial-
college/administration-and-support-services/hr/public/salaries/job-families/AR
---London-SP-Rates---2017-18.pdf)

~~~
goialoq
Glassdoor ignores equity in its averages, which is substantial portion of pay.

~~~
LeifCarrotson
I suppose equity, and the risk and complexity of it, are rather difficult to
condense into a number on Glassdoor. I would place an expected value on equity
at a lot of the places which are using AI at a small fraction of list price.

On that note, are there financial institutions and tools that let you
essentially take out a reverse insurance policy against your equity? They get
the equity which may be worth a mint in 10 years, or maybe nothing, you get
$XX/month cash?

------
Lazare
Traditionally, universities have paid less, but competed by offering an
excellent environment, working conditions, tenure, etc.

More recently, the working environments of most universities have become much
much worse; even exploitative. Tenure is much harder to get, more and more
classes are taught by part time adjuncts, the administration bureaucracy
becomes ever larger and more powerful. Horror stories are everywhere: The
frantic scramble for jobs, the poverty wages, the professors sleeping in their
cars or turning to prostitution to make ends meet, the politicised witch
hunts, the grinding bureaucracy.

In Pantic's story, their student was probably hired way for a salary in the
$125k-$250k range. Yes, that's high, yes it's more than a university is
probably able or willing to offer. But a lot of people are not motivated only
(or even primarily) by money. If you pick a top phd candidate, and make it
clear to him that there is a real, viable path towards him obtaining tenure,
making maybe $60-80k, having a well equipped lab, and having grad students of
his own, and that he'll be a respected, high status individual in the campus
hierarchy...many, many people would take that deal in a heartbeat. And that is
something which _was_ on offer 40 years ago, and is _not_ an offer now, but
could be. (Universities are still well funded; what's changed is the
priorities.)

There's no shortage of people who want to be academics; the problem is that
the deal being offered to them today is _terrible_ ; it's no surprise that the
few who have compelling options outside academia are tempted. Boiling it down
to being all about money is tempting, but I think it missed the point. If the
Guardian had bothered to track the student in the story down, I suspect money
would be a part of it, but only a part. And maybe not the largest part either.

~~~
pjc50
> If the Guardian had bothered to track the student in the story down

Good point. Sometimes "both sides" journalism is ridiculous, but in this case
it's very relevant and they didn't even have an "X couldn't be reached for
comment".

As you say, the academic environment is only suitable for people who _really_
want to be there and can put up with the terrible pay, uncertainty and lack of
choice. If you're not interested in that then there are few good reasons to do
a PhD, as it's essentially an extended work-sample interview for the process.

This isn't even an entirely new problem. The finance industry has been
offering people much better pay for certain kinds of maths for _decades_.

------
alvis
As an Imperial's PhD and having spent couple of years doing research there, I
can say that big salary is not essentially the main factor. Certainly it is a
factor, but probably not as big as Pantic thought.

The most important factor is the environment. All researchers love an
environment which encourages idea exchange. But the university (& the
department) doesn't seem to see the point. The environment is not comfortable
to work in to begin with, not to be mention about productivity and exchange,
though, to be fair, it is a common problems across all academic institutions.
So, if you want to keep them, give them a good environment please.

------
wolfgke
To me the solution seems simple: if you were to ask some AI scientist whether
he is still willing to work for the university, too, i.e. give lectures (but
as block course, so that is is compatible with the job requirements of the
main job) and additionally has the option to get a tenured position anytime, I
believe there are few that would not agree.

The problem rather is:

\- Why require the scientist to invest a lot of time (thus opportunity cost)
before they can get (very unlikely) a tenured position when they have the
alternative to earn lots of money in industry now?

\- Even if they are somewhat idealistic and would actually like to give
lectures - why not offer a format such as block courses (this format is not
uncommon in Germany) that fits better the industrial obligations than one
lecture per week over a semester?

I believe both issues can easily be solved by the university without having to
invest lots of money.

------
adamnemecek
The idea of a university needs to be restructured. Maybe this will motivate
them to do so.

E.g. unbundling would be a great idea. Also make teaching a class less of a
lifestyle choice and more of a "we made sure this person knows his/her shit".
Taking classes from people who have a lot of industry experience would be
dope.

Also setup research institutes like Inria of fraunhofer. a lot of good
researchers become professors to do research but don't give a fuck about
teaching. Which sucks for everyone involved.

~~~
adregan
Unfortunately, just because you know your shit, it won't necessarily make you
a good teacher. Teaching, to me at least, often felt less about the subject
and more about empathy. It's very hard to become a great teacher.

~~~
adamnemecek
Indeed. But being a professor doesn't mean you are good at teaching either.

~~~
adregan
Certainly. And that may have something to do with the fact that in some fields
of study, teaching is the only way to support yourself, so you get some lack
luster teachers.

------
jdhn
This reminds me of what happened during the fracking boom in North Dakota.
Students in school who were learning how to drive or repair trucks would
complete about half the course, and then leave because the pay was phenomenal.
Eventually instructors started leaving as well due to the huge bump in pay
they could make.

Personally, I think that Professor Shanahan did the best thing. He gets a
major pay raise while still retaining his scholastic position which he can
fall back on in case his private sector job goes kaput.

------
fatjokes
I work in the field of machine vision where Maja Pantic also contributes. It's
deeply disturbing to hear her say that. I don't know how she treats her grad
students but proposing that their pay be limited so she can keep them like
serfs is infuriating and really says a lot about the professor/PhD-student
relationship.

------
fatjokes
Pay caps? I'm sure the companies would love that; make a legal requirement
something they were fined for colluding on.

~~~
walshemj
Oh noes we in the UK have paid scientists and engineers poverty wages for
generations - now when they are in demand, we want the government to put those
boffins and greasy engineers in there place - cant have decent chaps who did a
PPE at Oxbridge getting paid less than those middle class oikes

~~~
peoplewindow
In this case it's not classism, though. The person calling for it is a
computer science professor. Her motivation appears to be preventing people
leaving her own domain and management hierarchy, rather than engaging in some
battle of the backgrounds.

~~~
walshemj
He has been co opted by the establishment this is the same old story favoring
broadly the liberal arts over Science and engineering

------
mrkstu
Industry is going to have to be careful not to eat their seed corn. There
won’t be high quality candidates for the next round of hires if they remove
the best professors from circulation.

~~~
emiliobumachar
The tragedy of the commons applies in full force. Each company is just
negligibly affected by their own behavior.

~~~
Filligree
Each company is positively affected by their own behavior, and negatively by
everyone else's.

It's a tragedy of the commons, yes, but traditionally we've used government to
handle these. Would that be desirable here? What form would it take, even?

------
ptero
I do not see such a big problem. There are always hot technologies (that
sometimes turn into fads) for which industry tries to grab anyone they can
find. This happened before (dotcoms, oil/fracking, synthetic bio, etc.) and
will surely happen again.

Those do not make a major negative society impact because they tend to be
narrow -- e.g., the current one sweeps in just AI/ML, not all of CS.

This means that while there are a few minor short term disruptions (e.g., a
new student might find a scarcity of professors in his #1 choice area for a
year or two), it opens up a bunch of opportunities, too (tenure spots, grants,
etc.) and in the super-competitive world of modern research universities they
quickly get a bunch of qualified applications.

My 2c -- best of luck to those who move to industry, but society impact will
be minimal if any 10 years down the road.

------
k2xl
Many of these top tier students are moving to the big companies not just
because of the salary, but also because they often have resources that is
better than any university can offer.

I don't think innovation is being stifled. Every week there is a new amazing
publication on AI/ML, but instead of coming from University it sometimes comes
from DeepMind , Google, FB, etc...

If you want to research self driving cars, wouldn't you want to work at Google
which has tons of data?

~~~
CJefferson
The problem is, all this company research is locked behind secrets and
patents.

No-one outside Google knows how deepmind works. No-one can reproduce it.

~~~
mathgenius
They published their Go algorithms in Nature. Also they put stuff into NIPS.
So I don't think this qualifies as "No-one outside Google knows how deepmind
works." If their stuff can't be reproduced, then it isn't science and the
journals shouldn't be accepting papers from them. Or am I not understanding
something?

~~~
kuschku
Try getting the training dataset they used.

For anything, actually.

They train all their networks on data taken from users, and publish neither
the data nor the models. And the scientific world doesn't have the resources
to replicate anything close to it.

~~~
mathgenius
Alpha Go (the earlier versions) was trained on publicly available games.

~~~
kuschku
That is a lucky case then, because for their NLP projects nothing is publicly
available. It's quite annoying if you can't get anything.

------
SomeStupidPoint
I've always been curious -- what's the best way for people in industry to help
with this problem?

I'm not going to compete for a lottery ticket to take a _huge_ pay cut to go
work as a professor, with fewer resources and a worse schedule than even mid-
level SDEs have. That's clearly not a workable solution for having the best
and brightest train the next generations.

But I am concerned by the prospect of a brain drain in the training pipeline
and am interested in helping with that. What are viable strategies to try and
share some expertise back from industry?

Setting aside for a moment if my employer would agree or not, what should I
even be pushing for as a collaboration/training program?

------
sevensor
Like jdhn elsewhere in this thread, this reminds me of recent history. I was
an undergrad in computer engineering during the dot-com boom, and classmates
would vanish halfway through, having been lured away by fat paychecks. I spent
1999 and 2000 wondering if I was making the wrong move by sticking it out. By
the end of 2001 I was pretty happy with my decision.

------
YeGoblynQueenne
In the UK, a degree is four years, a PhD three and a Master's one so I don't
see the big advantage of leaving your studies _right now_ to go work in the
industry. Why not wait to get your degree, then negotiate an _even bigger_
salary, with it at hand?

I guess there's a huge amount of hype about statistical machine learning right
now and some people will think they 'd better capitalise on it while it lasts.

Still, that's short-termist. If they hype ends soon, the majority of those
students leaving their degrees will find themselves out of work _and_ without
a degree. If the hype doesn't end soon then there's no need to rush.

So in any case, there's no need to rush. You'll get a better long-term deal if
you stay where you are.

------
driusan
For pretty much my whole life universities have been telling people that they
need to go to university to get a better job (where "better" == "higher paid",
sometimes implicitly and sometimes explicitly phrased that way.) I can
probably count on one hand the number of times I've heard anyone phrase
university in terms of civics or pursuing knowledge for the sake of knowledge
or anything other than "you need to go to university to get a better job."

This seems to be a case of them getting angry at people for having listened to
them. If you tell people that the reason to go to university is to find a
higher paying job, it's not their fault if they don't value your university
once they find a higher paying job.

------
BeetleB
Every so many days we get a submission on how difficult it is to get a TT
faculty position at _any_ university, let alone a top one. We keep hearing how
saturated academia is.

So why the concern here?

What will these PhD students gain by staying, when it is so saturated? It
appears this is more about tenured professors not being able to pump out
papers as easily as they could in the past. For them, the students are merely
tools to do so.

As someone else commented: Where is the student's perspective in this piece?
Many, many PhD students, if given a much better prospect at a TT position at a
university, would reject large salary offers.

------
nanodano
It's the same reason they can't get good security experts to teach at
universities. There was a study of 121 top universities and none of the top 10
require a course, top 3 didn't even offer an elective. Only 3 of the top 50
required a single security course.

[https://www.cloudpassage.com/company/press-
releases/cloudpas...](https://www.cloudpassage.com/company/press-
releases/cloudpassage-study-finds-u-s-universities-failing-cybersecurity-
education/)

------
nshm
Universities should sell scientists like clubs sell soccer players - best ones
for many millions. That would help to support the rest ;)

------
Ericson2314
Deep learning is alchemy so...oh well. Let the next winter fix this. Until
then, milk 'em the best you can, grad students!

------
kryptiskt
This is great, the usual problem in academia is senior faculty clogging all
the positions and blocking young researchers.

------
julianmarq
Just throwing this out there, and it might be overly optimistic and even
utopic, but wouldn't laxer intellectual property laws help with this? It could
mean that these people could share (more of) their work, no matter where
they're working.

------
hourislate
I know this was a UK School but when a University can pay a football coach
several million a year but can't pay a doctoral student doing research a
living wage, well there is a problem.

I just wish the Apple, Facebook, Amazon, MSFT, Google could get together
somehow and provide an alternative to the system we have now. The disruption
would be welcomed among the millions of students and tax payers with open
arms.

------
RestlessMind
> Beyond getting the companies to pay their taxes, Pantic said the government
> might have to consider pay caps...

Today, you are losing top talent to another company in your country. Tomorrow
with that kind of attitude and "solutions", you will lose them to another
country. For better or worse, money is one of the top motivators and the
society just has to deal with it.

------
jhbadger
This happened in the 1990s too. With any sort of computational talent not just
AI. Professors were leaving for industry all over. But then 1) the dot-com
bust happened 2) A lot of former academics realized that despite the nice
salary, working on a platform to sell pet food online or whatever wasn't
exactly intellectually stimulating. So it sorted itself out in the end.

------
tbhoc
The article is very dramatized and partly fictional. Pantic had no students
that left for Apple, dropped their PhD at the last year or earn 100k.

------
pfortuny
The consequence of turning academia into a competition against private
companies.

No more no less.

------
limaoscarjuliet
Flip side: if AI research is hurt, AI will not take over the World anymore! :)

------
away2017throw
Always puts a smile on my face when a smart person gets the money he deserves!

------
top256
it's comparing apple to oranges. At the risk of stating the obvious, academia
is not a good way to get rich imho. That is hardly new :)

------
rdlecler1
Not only Univiseristies, but startups are at risk. If I develop AI talent and
then Google steals them away with a $500k signing bonus what will this do to
the startup ecosystem?

~~~
notyourday
HTTP/1.1 402 F_YOU. PAY_ME

