imaginaryunit

Your point is well-taken and (thankfully) there are safeguards in place at top journals. However, Rob Tibshirani examined this a while back with a case study and came up with some unsettling conclusions about reproducibility: http://www-stat.stanford.edu/~tibs/FL/report/. The case study highlights the importance of debugging not only code, but also the entire experimental process.

"In academia, the end product is a publication and your code needs to work only once."

In my experience as ex-academic, the above is all too true in too many computational fields (and many sub-fields of CS). So I ask what scientific value (or any kind of value, for that matter) is being generated by grinding out publications with results that won't be repeatable?

We've found that Bump often requires several re-bumps, whereas QR codes can be reliably scanned within a few seconds. Also, we enable referrals of contacts (and real-time notifications thereof) with a single touch & click gesture.

My 2c as someone who has a similar background to yours (did PhD, post-doc, now an entrepreneur): a startup is in most ways more fulfilling than an academic environment. I think startups force you to be good at many things whereas in an academic environment, you're rewarded more for being the expert in a single narrowly defined subject. I do have to say though, given the way fields are getting narrower and narrower and the way the academe has devolved, I see little real connection between stuff being shown in academic research papers and the technology that we'll be hyping in 2032.

What I get from pg's comment is how the research experience has become less fun across the board in the last few decades (I'm focusing on post-graduate research, but a case could be made for undergrad research too). There are many reasons why this has happened, but the major outcomes are that:

-Publication pressure makes it such that research progress has become significantly harder to gauge (e.g.: it's become uncommon for results to get reproduced) across many fields (statistics, machine learning, the health sciences, which I've done work in for over 7 years at a highly respected institution)

-Balkanization of research fields where problems become increasingly exotic and narrowly focused to the point of being contrived (all the better for publishing papers of course)

-Increased difficulties in securing research funding or employment (more temp jobs though);

-Arbitrary metrics often being used to judge one's work. Example: if you do theoretical work, reviewers can reject your paper for lack of "applications"; if you do applied work, they can reject for "lack of theoretical depth" (what either of these terms mean in 90% of cases is arbitraily defined by a single reviewer who just wanted to torpedo your work).

-In some fields, entire mafia groups have formed that rigidly control the review process for that field, which means good luck to you if your work competes with theirs and you're submitting a paper/applying for grants

-Lack of accountability as to how research dollars are spent (vis-a-vis the public's interests)

-...

BTW, I say the above as someone who did a lot of enjoyable open-ended research as a grad student.

Minor point that has always bugged me: why doesn't Cocoa have native implementations of tree data structures?

We recently developed a way to get rid of paper business cards and their shortcomings (e.g.: clutter). It's called Napkkin, and it lets you create a business card on your phone and swap it with people you meet by scanning a QR Code. You can get referred by your new contacts and get notified in real-time so you can track who's helping you with word-of-mouth referrals.

We've got mobile/desktop web apps and Android/iPhone native apps set up. We're looking for feedback, so let us know what you think!

Feynman's view on CS is similar by Hal Abelson's take on the term (see http://www.youtube.com/watch?v=zQLUPjefuWA). Abelson's point about CS being more like magic has always stuck with me.

Though the gov't might want research to be distributed, the underlying problem here has more to do with the scientists themselves than anything else. We've had ArXiV around for a long time and yet I ask who's adopted it other than mathematicians and (many, but not all) physicists? Why hasn't it been adopted by NIH-funded life scientists?

The fact that years ago, life scientists easily could have adopted an ArXiV-like model for publishing, and chose not to, is quite telling. It suggests a far deeper problem with incentives in (general) academic culture to publish and that article availability is not going to affect that at all. As someone who spent >6 years Ph.D./PostDoc (bioinformatics, stats and CS), I can say that the vast majority of researchers have no genuine incentive to take action. Protesting against Elsevier online in the comfort of your office is one thing, but having to publish X>10 papers/yr to get tenure/brownie points within your department is another.