Welcome Anne, Ben, and Joe - <AUTHOR> http://blog.ycombinator.com/welcome-anne-ben-and-joe <comment><USER2> I think it's been long enough to conclude: the pg -> sama transition has been a clear success.

YC has innovated in a lot of really promising ways, expanding the partnership, expanding access, scaling successfully, and doing some new things.

Succession is one of the biggest challenges in organizations, and navigating it successfully is a big win.

<comment><USER3> Wow, you're jumping to that conclusion already? As much as I'm sure the three of them are great additions in a lot of ways, none of them has led a product to a meaningful exit just yet (Pinterest, 123andme and Airbnb have yet to exit).

Now their valuations are sky-high, and they've raised an incredible amount of money, but it seems like a big chunk of YC people (people working for YC, not in the program) haven't really successfully led a company to a big exit (IPO or $100m+ cash buyout).

PG: Sold Viaweb for ~$50m

Sam Altman: Sold Loopt for ~$43.4m after raising ~$30m

Anne Wojcicki: Raised $191m, no exit

Ben Silbermann: Raised $1.3bn, no exit

Joe Gebbia: Raised $2.3bn, no exit

I'm sure they're all very bright people, but at the end of the day, these aren't companies that have been profitable or really been sustainable. They're great resources for how to raise lots of money, sure, but are they people who can speak at any great lengths about building a long-standing business?

I don't mean to sound incredibly negative about YC; I want to keep a level head when looking at them and what they offer.

<comment><USER4> The first part of your post complains about how few YC partners have led a product to a meaningful exit, but the last part complains about how they lack experience building a long-standing business. The two of them are to some extent mutually exclusive: once you exit, you are no longer building a long- standing business. (There are some exceptions where a company is acquired and then continues growing under the acquirer, like YouTube, Instagram, Twitch, and Reddit...and founders of the latter two happen to be YC partners.) Which do you care more about?

For building a long-standing product or business, I would argue that Pinterest, AirBnB, 23andMe, GMail, and Yahoo Mail all qualify, as does YC itself. That's _why_ they haven't exited: Ben/Joe/Anne are all still building their businesses.

For exiting: PG/TLB/RTM (Viaweb), Kevin Hale (Wufoo), Justin Kan (Twitch), Michael Siebel (SocialCam), Paul Buchheit (FriendFeed) and Alexis Ohanian (Reddit) all exited for F-U amounts of money. Sam Altman (Loopt), Dalton Caldwell (iMeem), Garry Tan (Posterous), Qasar Younis (Talkbin), and Geoff Ralston (Lala) may have, but it's unclear from public documents whether the acquisitions of their companies resulted in a significant payoff to them after the liquidation preferences of their investors are taken into account.

<comment><USER5> It's sort of interesting that the inescapable conclusion is that VC funds power tech. What I mean is, if a business isn't sustainable, and the fact that they're sustainable doesn't matter, then it's thanks to the VC funds.

If you want to affect the world through business, the type of business you'll start is a startup. Counter-intuitively, it may be true that sustainability doesn't necessarily matter for a startup. If so, then sustainability in business doesn't matter for affecting the world.

That seems like dangerous thinking, and I've been trying to escape the conclusion. But since the home runs are how VCs make their returns, why is it a bad thing if 9 out of 10 startups eventually fail? And if it's not a bad thing, then why decry companies for being unsustainable, or the valley for funding them?

</comment></comment></comment></comment><comment><USER6> We keep seeing impressive names come on board as YC partners. This might sound strange to you guys, but I'd love to read about some no-name partners come on board as well. I've found that a lot of the most helpful people out there are mostly unknown and under-appreciated (think: corporate version of "guy on couch" in Half-Baked).

Maybe those people are just so stealthy that I don't notice that you're staffing up in that area as well. Just a thought!

<comment><USER7> YC is no longer a quaint little outsider experiment. They are now The Man, The Establishment, The Gatekeepers.

What will rise up and be the new YC for unconnected 18 year olds? YC probably wouldn't even talk to Steve and Alexis under the current expanded growth model. pg grew their idea and seeded their initial user base from his personal website readership.

I think Sergey once mentioned (jokingly) he's not smart enough to be hired at Google anymore. That's kinda the YC situation, isn't it? The original people of YC created something bigger than themselves, and maintaining+growing the behemoth machine is the focus now. The people who "grew up" inside YC run it now because they helped _create_ it. But, as an outsider, you can't just be hired into the machine. You can't grow the same way the originators did—you have to prove your worth elsewhere (this parking spot is already taken).

There's always space for new scrappy teams to out maneuver established organizations. What would a new "the next YC" look like? You probably can't start it as a tech industry outsider. You'll need to have had your VC connections and an exit or two already under your belt. The easiest route would probably be to round up a team of traitorous YC partners who say "this has grown too big and crazy, we need to reset our roots back to the original problem space again."

<comment><USER8> [http://fellowship.ycombinator.com/](http://fellowship.ycombinator.com/) :)

<comment><USER9> I suspect that most of those who were accepted were highly credentialed (either via brand name schools or former employers). It would be wonderful to be wrong about that, though.

<comment><USER10> Thankfully what you suspect is wrong here.

<comment><USER9> Good to hear!

</comment></comment></comment></comment></comment></comment><comment><USER11> Wow, very impressive additions. Given the size of their existing companies, will it be difficult to dedicate time to YC? Not only for the new partners but for all existing partners that maintain an executive level position.

</comment><comment><USER12> What is a CPO? from wikipedia:

Chief People Officer, an executive who oversees human resource management and industrial relations operations for an organization

Chief Privacy Officer, an executive responsible for managing issues of privacy laws and policies

Chief Process Officer, an executive responsible for defining processes rules and guidelines for an organization to follow

Chief Procurement Officer, an executive responsible for supply management

Chief Product Officer, an executive responsible for product management and development

<comment><USER13> >@airbnb Co-founder & Chief Product Officer. I design things.

[https://twitter.com/jgebbia](https://twitter.com/jgebbia)

</comment></comment><comment><USER14> I see these announcements from time to time and not knowing that much about how YC operates, have no idea what something like this means for the companies accepted into YC.

Can someone shine a light on what these three people (and the other partners) will do in a practical sense?

<comment><AUTHOR> It means YC companies will be able to meet with them one on one and get advice. They get a slice of YC equity in return.

<comment><USER14> Ah understood. Is it something like the company feels like it needs some help in the area of design and sets up a meeting with a design-minded partner? Or does YC look from outside and say, "you could use some help in the area of design, so maybe talking to so-and-so is a good idea". Or a little of both?

</comment></comment></comment><comment><USER15> The part about Ben being a two-time YC alum caught my eye. In practice, what does that mean?

I was under the impression that even once YC technically ends, founders are still allowed to schedule office hours if it suites them. If so, what does that person receive from returning to YC?

I presume (1) the opportunity to have the advice geared towards a new company, not the old one (2) access to the dinners for that session, and (3) the ability to bring in new partners to YC.

Roughly accurate?

</comment><comment><USER16> _Ben Silbermann is the cofounder and CEO of Pinterest, and a two-time YC alumni._

Shouldn't it read instead "[...] and a two-time YC _alumnus_ "? Just saying!

</comment><comment><USER17> Will be nice to demo cryptography apps with Anne and Ben. :D

</comment><comment><USER18> Are there ever posts about who has left? Has anyone left?

</comment><comment><USER19> Joe is a rockstar! Great addition.

</comment><comment><USER20> The fact that we're welcoming Anne, Ben, and Joe, is why we need ethics in welcoming Anne, Ben, Joe.

</comment><comment><USER21> With respect to Anne joining, would Google find out about applying startups?

<comment><USER22> I'm not entirely sure the source of the question but you know she's divorced Sergey right?</comment></comment>


'We can't compete': why universities are losing their best AI scientists - <AUTHOR> https://www.theguardian.com/science/2017/nov/01/cant-compete-universities-losing-best-ai-scientists <comment><USER2> 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.

<comment><USER3> 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?

<comment><USER4> 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.

<comment><USER3> > 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.

<comment><USER2> 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.

<comment><USER3> > 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.

<comment><USER2> > 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.

<comment><USER5> 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.

<comment><USER2> 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.

<comment><USER5> >> 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.

</comment></comment></comment></comment></comment></comment></comment></comment></comment></comment><comment><USER6> 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.

<comment><USER7> 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.

<comment><USER8> 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.

</comment></comment></comment><comment><USER9> > 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)

<comment><USER10> Glassdoor ignores equity in its averages, which is substantial portion of pay.

<comment><USER9> 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?

</comment></comment></comment><comment><USER11> 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.

<comment><USER12> > 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_.

</comment></comment><comment><USER13> 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.

</comment><comment><USER14> 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.

</comment><comment><USER15> 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.

<comment><USER16> 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.

<comment><USER15> Indeed. But being a professor doesn't mean you are good at teaching either.

<comment><USER16> 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.

</comment></comment></comment></comment><comment><USER17> 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.

</comment><comment><USER18> 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.

</comment><comment><USER18> Pay caps? I'm sure the companies would love that; make a legal requirement something they were fined for colluding on.

<comment><USER19> 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

<comment><USER20> 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.

<comment><USER19> He has been co opted by the establishment this is the same old story favoring broadly the liberal arts over Science and engineering

</comment></comment></comment></comment><comment><USER21> 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.

<comment><USER22> The tragedy of the commons applies in full force. Each company is just negligibly affected by their own behavior.

<comment><USER23> 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?

</comment></comment></comment><comment><USER24> 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.

</comment><comment><USER25> 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?

<comment><USER6> 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.

<comment><USER26> 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?

<comment><USER27> 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.

<comment><USER26> Alpha Go (the earlier versions) was trained on publicly available games.

<comment><USER27> 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.

</comment></comment></comment></comment></comment></comment><comment><USER28> 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?

</comment><comment><USER3> 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.

</comment><comment><USER5> 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.

</comment><comment><USER29> 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.

</comment><comment><USER30> 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.

</comment><comment><USER31> 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/)

</comment><comment><USER32> Universities should sell scientists like clubs sell soccer players - best ones for many millions. That would help to support the rest ;)

</comment><comment><USER33> Deep learning is alchemy so...oh well. Let the next winter fix this. Until then, milk 'em the best you can, grad students!

</comment><comment><USER34> This is great, the usual problem in academia is senior faculty clogging all the positions and blocking young researchers.

</comment><comment><USER35> 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.

</comment><comment><USER36> 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.

</comment><comment><USER37> > 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.

</comment><comment><USER38> 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.

</comment><comment><USER39> 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.

</comment><comment><USER40> The consequence of turning academia into a competition against private companies.

No more no less.

</comment><comment><USER41> Flip side: if AI research is hurt, AI will not take over the World anymore! :)

</comment><comment><USER42> Always puts a smile on my face when a smart person gets the money he deserves!

</comment><comment><USER43> 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 :)

</comment><comment><USER44> 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?

<comment><USER2> HTTP/1.1 402 F_YOU. PAY_ME</comment></comment>