I don't get this. The whole point of university research is that it is too risky (or benefits will be too far in the future) to make it profitable for companies to pursue. I don't see how anything could be too risky for the university, but not too risky for a business.

Edit: I'm not saying universities are perfect. I'm just saying that they still manage to do research that is too risky for industry. For example: finding the higgs boson. I don't see any examples of industry doing research that is "too risky for the university."

Everything you do as university research is towards the aim of getting publications to progress either you or your adviser towards tenure. The problem is that things that don't work are not usually publishable. This leads to 'fluffing' up results (read enough academic papers and you'll find some hilarity there) and avoiding anything that might not pan out.

Just as important is funding, even a small lab with a few computers and one or two grad students needs funding. And in CS that largely means DARPA or a handful of other government agencies. If your particular research interest involves eventually killing someone, you'll do fantastic. There are of course other sources of funding but they typically have much smaller wallets, especially the further you go on the 'for the good of humanity' scale.

I've seen countless times were grad students are doing something really interesting, but because it's not going to help anyone get tenure and not going to bring in any funding, these students are strongly encourage to 'get back on track'.

Unfortunately, being in the EU, I don't think changing this part fixes that many of the problems. EU grants are not about killing people, but typically about cooperation, building understanding between nations, reducing violence, integration of immigrants, that kind of thing. Goals I like more, in principle, than DARPA's. But the actual administration is if anything worse: 100-page proposals via hugely bureaucratic processes (NSF's are at least only 15 pages), unwieldy multi-country consortia, periodic mandatory status update meetings in Brussels, the works. If you can sell what you're doing within that framework and work with it, it's good, but it's still very much about being on the right track to impress the purse-string holders.

Tell me about it. I was 7 years in "academia" in the EU and 4 of those years was working in a FP7 (Seventh Framework Programme) project. Man, the amount of administrative baggage we have to do is amazing. "Libre research" is a myth, between monthly deliverables, 6-month review, half-way Brussels project review, you could not make a lot of research.

And then you have all the administrative controls, I kid you not, I had to log what I did every day in two places (one in EU FP7 timesheets (in Excel), and another one in my institute's own software (a terrible java program)). Sure, the upside was that I got to travel a lot (the project had about 7 participant countries).

Now I returned to the industry, I am in a company from the Silicon Valey as a "simple" software engineer (even though I have a PhD) and I could not be happier. Moreover, after a couple of months in the position I have made several contacts which are bringing new opportunities.

I am happier at my current "fast paced" job now as I was while I was in academia doing papers just trying to publish papers for the sake of it (that is how I felt).

Of course this doesn't get you out of the trap of having to do research in the area of interest to whatever large company is funding you. You can do research that isn't indirectly getting people killed ;) but it usually has to be pretty clearly aligned with the business interests of companies funding the research

I was just curious because my impression is that CS is rather well funded, especially for having far lower expenses than anybody else in college of engineering.

I get it. I recall specifically posing a promising, if not clear-cut, research topic to my grad school advisor and his response "that's high risk".

Academia is more concerned with the volume of publications rather than impact and unique ideas. There are tremendous disincentives in the system for innovation.

As a generalization, this is false. Certainly there is more emphasis on publication than is warranted, but most of the top places care much more about impact/reputation than about raw # of papers or citations. If you talk to people about how research labs hire newly-minted PhDs, how faculty are hired, or how tenure decisions are made, everything I've heard suggests that, at least for good places, they aren't just looking at the length of your pub list or the # of citations.

I feel that's overstating it but even if not, is it worse than industry? I've found academia to be very accepting of different viewpoints and depending on the field, experimentation is encouraged.

In my viewpoint, if an advisor in academia calls something 'high-risk' it's within the context of the overall work. For example, in grad school, the aim is to make a contribution to the field and get a PhD. Several students I've known have followed 'promising' lines of work (after disregarding advice to contrary) and ended up with nothing.

His essay seemed to say that the cautious incrementalism and turf-buildout that succeeds well with NSF (where most of the funding for academic ML research comes from), turned out to be less exciting than riding upon the Google juggernaut.

It's hard to argue with that. The applicability of ML technology has attracted companies with deep pockets, and really changed the landscape of research.

He claims universities are increasingly judging professors by their ability to get funding. And, due to budget cuts, funding is only going to areas likely to pay off. "Too risky for academia" would be too far off the beaten path to get funding.

That said, I don't know if it's true or not.

What's increasingly hard to do in academia is to take risks individually: if you decide something is under-researched and should be a priority, rather than waiting for a funding agency to decide it's a priority, you'll have tough going.

In fact, the same can be said for some of the academics working in national labs.

What's happening at CERN is not at all reflective of the university environment of the OP, which emphasizes small collaborations working on, say, million-dollar projects lasting 3-5 years. As we both know, CERN is nothing like this.

I commented because the idea of saying that the work at CERN is "university research", as was done in the comment above, is mistaken. CERN has no relation to the work done by the OP.

So, that probably isn't the best example to use.

The LHC on the other hand is one example of what the original post was worried about - the trend towards more consolidation, towards funding bigger projects (with fewer people), at the expense of many smaller labs.

The public draft was also of much higher quality then Celera's, and as hindsight shows, also born of better scientific technique. Celera secretly used only one person (very nearly) to sequence from, rather than a collection.

If Celera never existed, the human genome would still have been completed in a similar timeframe and shotgun sequencing would still have been adopted. If nothing else, academics are just as competitive as anyone else and thus some lab would have loved to show the feasibility of shotgun sequencing, albiet on a different species.

Disclosure: I worked on the public draft and also had access to the Celera draft right around the time that the genome was "completed". Our lab was using and comparing both the public draft and the Celera draft at the time. We were even fusing the two to get the best possible "up to the minute" draft for a specific chromosome.

When you think about the sums involved, we could have done a whole lot of smaller, riskier projects, which may or may not have panned out but had a great deal more potential. Which I guess is your point.

The LHC is a big, expensive piece of infrastructure that groups have to share, but there are multiple groups.

Centralization of resources is not necessarily a bad thing.

yeah i guess industry isnt really accomplishing much these days

(How are your examples actually useful?)

It is for this reason that I believe there is still a place for academia in our society.

In some fields, this is very easy. It's easy to buy a bunch of cluster time on Amazon EC2 or something and run lots of machine learning/other research applications. This is awesome and is one of the great things moving the field forwards.

It is much more difficult in the physical and life sciences where starting out costs are extreme. Many great ideas do not become reality because of how expensive starting a company in those fields are and how difficult it is to raise money in those fields. Lots of VCs are cutting funding in these areas because of the comparatively high risk and pharmaceuticals are slashing R&D budgets in order to pick up smaller companies and secure rights to compounds, etc. Funding is very difficult in these fields and the framework of academia is sometimes the only reasonable way to carry out original research.