look I get it - ivies attract best and brightest and the incentive structure for businesses is such that things like this make sense (as a recruitment tool) but why not drop this kind of program on a good-not-ivy state school? there are so many to pick from (um Ann arbor, ut Austin, UF, stonybrook, CUNY, etc). it's just strikes me as very similar to wealthy donors donating back to ivies - like c'mon what is marginal utility of that.
Princeton has an extremely strong mathematics department (possibly the best in the world) plus the IAS is nearby. Perhaps they are looking for close collaboration with pure mathematicians? My understanding is that there are not very strong theoretical underpinnings to most of the machine learning techniques in use today.
? I know people at most schools I pay attention to getting paid to specifically work on that. In fact this is what probably one of the most famous applied mathematicians in certain engineering crowds (Ingrid Daubechies) is working on for her big project from what i understand
> My understanding is that there are not very strong theoretical underpinnings to most of the machine learning techniques in use today.
I wonder how come this is the case from looking at ArXiv, it seems there are plenty of low-hanging fruit relating to the Foundations of Machine Learning.
There's probably some long-term strategizing going on here, as well. The likelihood of a CS undergrad from Princeton creating their own startup that cuts into Alphabet's margins somewhere is much higher than the probability of a student from a state school doing the same.
This probably had a lot to do with it. Schools like that have huge endowments (Princeton's is north of 20 billion dollars), and as such can afford to attract very good faculty. Very good faculty can lead to very bright students.
Princeton is also going to have a lot more defense dealings than something like a state school and where cutting-edge tech is being researched, OGAs are guaranteed to be sniffing around and weaseling their way into the research with funding.
That most likely has nothing to do with it. These sort of things happen with previous relationships of some faculty with academics inside Google. There is no "long term" play of let's quash the competitors.
Higher ranked schools are often better at research as well, you can get more bang for your buck than lesser ranked schools.
They want collaboration and access to great minds, not influence. Also, every if they did want influence, the ivy pay would make even more sense bc the ivy tail wags the academic dog. Better to influence a generation of future faculty than one Dept of current ones...
"Collaboration and access to great minds" comes from influence. As does the opportunity to shape postdocs and graduate students - the generation of future faculty you're talking about.
You make the huge assumption that only elite institutions produce high quality research. Especially for narrow specialties, this isn't necessarily true either.
> Higher ranked schools are often better at research as well, you can get more bang for your buck than lesser ranked schools.
Just to be clear, Princeton ranks close to 15-20th in CS. Many state schools do out rank Princeton in CS and they do not have such labs yet.
I can understand if IAS or the Math department was the main reason to open a lab there. But, if it was quality of CS faculty that exclusively factored into the decision, then there would be other state schools in the line ahead of Princeton.
It's not too surprising. Many Princeton faculty work closely with Google already. Princeton researchers are also known for being very theoretically focused, including the two mentioned in the article. If Google wants to diversity its research groups to include more theorists, then Princeton is a smart choice.
Google already has offices in Austin and Ann Arbor.
On the scale of things academics are pretty cheap so they can afford to have lots of offices and cover the top 20 schools. Really they should have one in New Haven as well.
The prestige thing is not as important (I believe). For instance they had offices in Austin and Ann Arbor before Princeton NJ.
The prestige thing is only important for client facing roles (McKinsey or Goldman want to assure the money people that they are in good hands).
It is kind of interesting, given that Princeton's not really at the top in AI (but it would be difficult to be, because they're so tiny--departments like Berkeley have a huge number of AI faculty).
But, at the same time, Google already has connections with Princeton, both through these individual profs and through the NY Tech campus (they shared an office with Google before moving to Roosevelt Island).
It is kind of interesting in the trend of professors being more connected with industry and spending time actually working at tech companies. It's both interesting from the perspective of engagement (profs can work on real problems) and frightening from the prospective of independence--the companies will inevitably sway which problems profs work on, and of course their students won't enjoy their advisors' attention being scattered elsewhere.
The address of the building is literally Princeton within city limits (according to Google Maps). Ewing is a bit too far. You might be thinking of the data center, though to be quite honest I don't remember where it is.
Princeton has an enormous mailing address area, though I have no idea how it got to be so. I grew up in the area and it sometimes felt like Princeton and Trenton were the only two mailing addresses in all of Mercer county
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[ 0.20 ms ] story [ 1314 ms ] threadGoogle (and microft and...) do support (fund) labs at most of the schools you listed.
Yes, particularly with regards to generalization. There's a large number of theorists racing to explain that.
I wonder how come this is the case from looking at ArXiv, it seems there are plenty of low-hanging fruit relating to the Foundations of Machine Learning.
To speak nothing of the professors...
This probably had a lot to do with it. Schools like that have huge endowments (Princeton's is north of 20 billion dollars), and as such can afford to attract very good faculty. Very good faculty can lead to very bright students.
Princeton is also going to have a lot more defense dealings than something like a state school and where cutting-edge tech is being researched, OGAs are guaranteed to be sniffing around and weaseling their way into the research with funding.
Higher ranked schools are often better at research as well, you can get more bang for your buck than lesser ranked schools.
Note that this depends on what you want for "bang". At less well-heeled schools, a far more modest donation can steer departments etc.
Just to be clear, Princeton ranks close to 15-20th in CS. Many state schools do out rank Princeton in CS and they do not have such labs yet.
I can understand if IAS or the Math department was the main reason to open a lab there. But, if it was quality of CS faculty that exclusively factored into the decision, then there would be other state schools in the line ahead of Princeton.
On the scale of things academics are pretty cheap so they can afford to have lots of offices and cover the top 20 schools. Really they should have one in New Haven as well.
The prestige thing is not as important (I believe). For instance they had offices in Austin and Ann Arbor before Princeton NJ.
The prestige thing is only important for client facing roles (McKinsey or Goldman want to assure the money people that they are in good hands).
But, at the same time, Google already has connections with Princeton, both through these individual profs and through the NY Tech campus (they shared an office with Google before moving to Roosevelt Island).
It is kind of interesting in the trend of professors being more connected with industry and spending time actually working at tech companies. It's both interesting from the perspective of engagement (profs can work on real problems) and frightening from the prospective of independence--the companies will inevitably sway which problems profs work on, and of course their students won't enjoy their advisors' attention being scattered elsewhere.