Postdocs in Copenhagen

I apologize for the short notice, but my occasional co-author Rasmus Pagh is looking for postdocs for a big data project he recently had funded, with an application deadline on April 14th. 

For more information, you can see this page, which starts with:

The Scalable Similarity Search (SSS) project led by Professor Rasmus Pagh is seeking 3 post-docs with a strong background in algorithms theory, combinatorics, or statistics. The project is funded by the European Research Council (ERC), runs in the years 2014-19, and will include a total of 3 PhD and 3 post-doc positions. The aim of the project is to improve theory and practice of algorithms for high-dimensional similarity search on big data, and to extend similarity search algorithms to work in settings where data is distributed (using a communication complexity perspective) or uncertain (using a statistical perspective). A post-doc position may include a long-term visit to a project partner (at Berkeley, Harvard, MIT, Stanford, or Tsinghua) if all parties find the visit beneficial.

Or you can see this nice video Rasmus recently put together.   

And yes, I'm self-interested in this matter, in that as someone who works with Rasmus, the potential "long-term visit" to Harvard described above would involve me if it worked out.  Also, Copenhagen is a wonderful place. 

Hashing Summer School in Copenhagen

Of the many, many interesting things happening in Copenhagen this summer (SEA, SWAT, ICALP) we'd like to add one more:  a Hashing Summer School at the University of Copenhagen.  Here's the web site.  This was the brainchild of Mikkel Thorup, who knows a thing or two or three about hashing, and is co-organized by me and Rasmus Pagh.  We've got a great set of speakers, and we expect a mix of lectures, problem-solving exercises, a poster session, and other such fun and learning.  The registration deadline is May 15th;  check the web site for details.  If you're coming out to Copenhagen for other activities, or just want a good reason to visit the beautiful city, take a look.  I hope to see you there.

Leslie Lamport wins Turing Awards

In another sign that these Turing Award committees really know what they're doing, Leslie Lamport has won the Turing Award.  There's a very nice writeup including the history of his work up on an official Microsoft blog post.

While I know there are arguably many people deserving of a Turing Award, Leslie Lamport is an amazingly obvious and absolutely fantastic choice.  His body of work is truly inspiring, and as the above links show, his work has had a huge effect on us all.   

ICERM (Brown) Workshop on Stochastic Graph Models

I'll be commuting throughout the week to the ICERM Workshop on Stochastic Graph Models.  ICERM is the Institute for Computational and Experimental Research in Mathematics, a new-ish place associated with and walking distance from Brown University, and Eli Upfal (among others) is making sure that it's closely connected with Brown Computer Science as well as other mathematical disciplines.  The building is very nice and new, with a great view of Providence.  It's also very close to the freeway.  (Driving to the ICERM building is not much more time than driving to MSR New England from my house, even though it's more than three times the miles...)

We've already had great talks today by several great people (Leslie Goldberg, Artur Czumaj, Susanne Albers, Flavio Chierichetti, and Gopal Pandurangan), and there's a fantastic schedule for the rest of the week.  If you're in the neighborhood you should come on by.  Leslie's talks on evolutionary dynamics on graphs and Flavio's on trace complexity of network reconstruction were both very close to long-time interests of mine, though it feels like it's been a while since I worked on such "pure" (and very pleasant) random process problems.  I can feel the talks drawing me in...

By the way, has anyone figured out the complexity of the 2048 game yet?  Assuming that the game uses some stochastic model at each step, I wonder what you can say about the probability of getting to 2048 under some model of play.  That's a stochastic model in need of analysis. 

Those who Hire vs.

If you haven't yet, I encourage you to read the Inside Higher Ed article about a department that, when a candidate they had made an offer to attempted to negotiate the terms of that offer, then rescinded that offer.

Let me be clear up front:  I'm on the side that finds the department's behavior reprehensible and inexcusable.  (As is often the case, I should acknowledge that I have only the limited information available.)  I admit I view this in the larger picture of the current state of employer-employee relations, where I think the scale has tilted too far in favor of the employer side.  Others have noted that there seems to be a prevailing attitude that current employers, by and large, feel employees should be grateful that they're having the opportunity to work for them, regardless of conditions.  For a recent example article expressing this, you can read this New York Times article on "My Life as a Retail Worker".  While tech workers may think they're in a happy state where employers need them so much that they have to treat them well -- something that, generally speaking, clearly has some truth to it -- I worry on the tech side that has made people complacent.  The ongoing story about how Google and Apple (as well as other tech companies) had a secret agreement not to recruit each other's employees demonstrates that, even in tech, the utility of workers and their employers may not always naturally align.  

Was the candidate in question asking for too much?  I think the candidate was negotiating;  she makes clear that she was not expecting to get everything asked for, but wanted to see what was possible.  The department chair (or whoever was in charge) should have explained what was possible from their standpoint, and set a deadline for the candidate to decide.  To rescind the job offer smacks of discriminatory practices -- not (necessarily) discriminating against women (an issue that has been raised in this context, since maternity leave was part of the request) -- but discriminating against employees that might think to advocate for themselves.  Many employers seem to call employees that advocate for themselves "troublemakers";  is that how we're to interpret the mindset behind the decision here?  That's disturbing -- as a general trend in academic life and specifically with this university's behavior.  I'd like to think people who self-advocate are desirable for tenure-track positions, not the opposite. 

Passing of the Professor

Sadly, "The Professor", Russell Johnson, has passed away. 

I enjoyed Gilligan's Island as a kid.  I can't help but think that his portrayal deeply affected people's perception of scientists, subconsciously or consciously, for better or worse, for a generation. 

Some related links.
Improbable research. 
TV Tropes (the Professor).

Feel free to add more in comments.

Andreessen Tweets

My brother pointed me to this article on a great exchange of tweets about the origins of Netscape. 

The two highlights, for me at least.  First, Andreessen expressed a philosophy that I believe in, but I don't think most university IP departments do:  in computer tech, the best strategy is for the university to let professors/students/other employees run with their entrpreneurial plans rather than attempt to maximize the university's short-term or nominal value extracted.  He tweeted about how the University of Illinois lost out on the browser/Netscape process, and tweets:

History of Stanford suggests best approach extreme laissez faire-optimize for long-term philanthropy vs short-term gain.

and

Many billions of dollars of gifts from grateful alumni far outweigh commercial licensing or patent arrangements in long run. 

I agree with the sentiment.  An issue is that this approach may not be best for some situations -- drug development at universities, perhaps (I don't know how that works, but I've heard it's "different" from an IP standpoint) -- although maybe even there a more hands-off approach from overzealous university lawyers would be best in the long run.  (Maybe I'm too optimistic -- after all, I suggested Harvard should be tuition-free and could still come out ahead.)

The other more amusing highlight is Andreessen notes that the Mosiac project applied for more NSF funding and was rejected, which pushed them to start a company.  Which, he suggests, was probably the right decision for the NSF.  Looking at the outcomes, there's a good argument.  Something for me to keep in mind the next time a rejection comes -- even Marc Andreessen had proposals rejected by the NSF, and he ended up doing OK. 

Boston Magazine Piece on Aaron Swartz

If you haven't seen it, there's a well-written piece on Bob Swartz, father of Aaron Swartz, in Boston Magazine, covering MITs reaction to Aaron Swartz's case.

The PhD - Tenure - Jobs Argument, Already Started for 2014

'Tis the season when graduate applications are being decided as well as the job interview process starting again, and just in time for the new year, your regularly scheduled inflammatory article entitled, "Can't Get Tenure? Then Get a Real Job" up at Bloomberg.  The point of the article seems to be that the tenure model follows the age-old "tournament model" of employment, with a very few plum positions at the top, and lots of people scrambling for them -- and, along the way, essentially turning themselves into free labor for existing tenured professors, as well as (in most cases) unemployable dried out husks by their early 30's -- and that's bad.  The only solution suggested seems to be to cut Ph.D. production, and there are no incentives to make that happen.  (I can only encourage you to avoid reading the comments, where somehow this becomes a political issue, with "liberals" being to blame for... seemingly everything, I guess, but this in particular.)

I'm always happy to admit that computer science seems to be a special case;  industry takes many of our PhDs.  However, without trying to dissect the article -- which is field agnostic -- I think it's healthy for computer science to regularly look at itself, and determine whether it's doing the right things.  Here's my take on what those are, at the individual (faculty) level:

1)  Be honest with undergraduates.  If you're a professor talking to an undergrad thinking about grad school, you should point out that you're the success story, not the average story.  Point them to the Taulbee survey or other figures.  Have them work out the math on potential opportunity costs.  Whether you're positive or negative on them going to graduate school is up to you, of course, but either way you should be giving clear, factual information as well as advice.
2)  Be honest with your graduate students.  If they aren't performing, let them know they need to get better (or move on).  (It's painful, but better for them in the long run.)  Be sure the latest "time-to-academic-job" timeline is on their radar -- how many years of postdocs is becoming the norm?  Make sure they know what skills they need to work on besides research skills -- speaking, writing, organizing, managing.
3)  Controversial(?):  encourage breadth for your students.  It seems to me that since I was a student there's much more pressure to go deep -- to show in your PhD that you are the expert on your research area, even if that research area becomes narrow.  The message seem to be don't waste time on classes, projects, or learning that fall outside your clear research path.  I'm torn in advising the other direction, because I think the way the academic field is progressing, that can be a promising short-term approach if the goal is to get a tenure-track position.  But I don't think it's good for developing a long-term career, and I don't think it's the right approach for the significant number of students who end up doing something else.  [I'm aware I'm very biased on this issue.]  

At the field level, I think there are big questions, and I'm not sure how they get answered.

1)  Are we encouraging too much depth over breadth in our training?  (See 3 above.)  Is this what we want?
2)  Are we OK with what seems to be a lengthening pipeline, with postdocs becoming more common (in some areas, but not all, standard) on the academic career path?
3)  Do we have any sense of goals for how many graduate students go on to careers in industry, entrepreneurship, teaching (e.g., teaching university positions as opposed to research university positions), etc.?  If so, do we want to do more to help prepare students for these types of work, which may not mirror exactly what we as professors do?  How do we measure success for our graduate students, and how do we tell if we're doing a good job preparing students overall?

Plenty to think about for the new year.

Tracking down the Harvard Non-Bomber

This year, (allegedly) a Harvard student performed the modern equivalent of pulling a fire alarm in order to avoid a final exam, in this case by sending an e-mail claiming that there were bombs in several building throughout the campus.  (One of many Crimson stories here.) 

I am proud to say that this student, who was apparently a psychology and sociology major or a prospective psychology major (according to Crimson reports), was (allegedly) using TOR and Guerrilla Mail to try to cover his tracks.  (See, for example, this article.)  I think it shows how Harvard has made it as a computer science/engineering school, now that even our psych majors know how to set up and use tools like this.  Years ago, before CS started taking off at Harvard, you would be hard pressed to come up with a student from a liberal arts major who could use tools like this.  It just goes to show how the place has changed for the better.  I like to think that, if he was a computer science major, and would have correspondingly more understanding of what tracks he was leaving (hint:  don't use your own computer through Harvard's wi-fi when sending a bomb threat...), he might have gotten away with it, or at least been a lot harder to track down. 

[Just to be clear, this is very tongue-in-cheek;  I in no way support or even really want to make light of what this student did, it's utterly reprehensible.  And as several colleagues of mine and I have noted, he knew just enough to be dangerous-- mostly, in the end, to himself.

Also, I was (again, along with several of my colleagues) 95+% certain right off the bat it was a student trying to escape finals.  Besides the timing, the 4 buildings named as where bombs might be hidden included 3 big lecture buildings where exams were taking place... and a freshman dormitory.  (In fact, MY freshman dormitory.)  It seemed unlikely that the dorm would be on any real bomber's radar, and seemed to me to be a clear signal that one or more students were behind it all.]   

Lesson of the Day

Saturday I took two of my daughters to see a musical at Harvard.  Amazingly, in the small theater, we were in front of a pair of students who seemed intent on talking throughout the performance.  (One male, one female;  the male did seem to be doing more of the talking.)  The volume seemed to increase until by the end of the first act they seemed to be talking at normal conversation level.

As soon as the curtain hit I turned and as nicely as I could (which was, probably, still with a snarl) that there were several bars and cafes available in Cambridge if they wanted to talk, but we were here to watch a show.  I got several approving nods from around the nearby audience;  in fact, about a minute later, an usher for the theater came over and appeared to be telling them to be quiet or get out, so others had clearly complained.

To their credit were apologetic and stayed quiet for the second act.  I can only hope that I helped teach these students the important lesson that conversing in a theater is a very bad idea -- probably more important that most of what I ever teach in class.  (Although how they managed to get this far without absorbing that lesson somewhere is, I admit, beyond me.)  My older kids already know that, but they got some useful reinforcement.   

Algorithmic Growth (Class Size)

Pre-term planning numbers are in for Harvard, and it looks like the undergrad Algorithms and Data Structures class has about 175 people planning to take the course.  That's a huge jump again over the last few years (where it's jumped from the 50s to well over 100).  I imagine the growth is spurred by our ever-increasing enrollment numbers in the intro classes, as well as the fact that it's being taken over by a younger, dynamic, new faculty member.  (Go Jelani Nelson.  I can't help but think some number of students were waiting for me to go on sabbatical...)

These numbers are usually within plus-minus 10% of the final, though there's higher variance when new instructors take over.  If 175 became the steady state class size, it would mean a bit over 10% of the students at Harvard would take Algorithms at some point.  I don't think I ever expected that when I started. 

If we can get the people resources, at some point we'll probably want to start breaking this up.  One direction is to make an "honors" class that would cover more/harder material more rapidly.  (We're thinking of making this an "honors theory" course, that would cover both complexity and algorithms -- 2 classes packed into 1.)  The Math department here has done this very successfully, separating out the future Putnam winners from other students early on.  A benefit is it leaves the remaining students happier as well, as the curve-breakers remove themselves from the regular class.  Another possibility is to do an algorithms style class designed for non-majors, that would bring in more people not currently taking algorithms as well as some of those in the current course.  There are "topics" classes like this -- the Easley/Kleinberg book Networks, Crowds, and Markets: Reasoning About a Highly Connected World is algorithmic and seems to allow an instructor to choose a desired mathematical level from a broad range -- but I don't really know of examples of something more like a standard algorithms/data structures courses designed for a broader audience than for CS majors.  I'd be interested in pointers to and anecdotes about experiences in such classes if they exist. 

News Worth Reading

There's been plenty of interesting stuff popping up in the news, so it's time to collect a bit.

This article describes a current patent case in cryptography, where apparently Ron Rivest testified (by deposition) and Whitfield Diffie took the stand.  While I can't help but wonder if the article has dramatized the proceedings a bit, it does give some idea of what patent trials are like.  I found it interesting both legally and technically.  Anyone interested in the legal/expert witness side of technical work should find it worthwhile.

Update:  The case was decided, as Suresh notes.

In other legal news worth noting, Google Books was found to be fair use.  The decision is online (and available at the link) -- I'd definitely recommend reading it if you're interested in fair use and the legal framework for how fair use is currently (at least of this decision) is understood.    

Harvard's CS50 course just made the Boston Globe business section.  I'll quote the conclusion from the new boss, David Parkes:  “There’s a new willingness among the student body to take risks, to not follow what has been the default path of going into medical school or going into finance,” said David Parkes, Harvard’s dean for computer science. “I think part of it is that students are seeing a new way to contribute to society through computer science”

Michael Nielsen put up a chapter of the latest book he's working on, on neural networks. 

I found myself more interested than I expected when reading the article How Academia Resembles a Drug Gang.  The issue of PhD overproduction is already well known, but this brought in a new dimension for me, with the discussion of "dualisation" -- employment systems with an "insider" class with unusually high benefits (supposedly, from the article, tenured professors) and a large "outsider" class of people trying to get on the inside and supporting their lifestyle (from the article, untenured part-time faculty and PhD students).  Probably worth thinking about in terms of trends in our field, but also just generally, I'm now curious about the economics.  Dualisation doesn't seem like it would lead to long-term stable systems -- what's the model?

I'll have to pay more attention to the news myself these days.  I was asked to serve on the Communications of the ACM editorial board, news division, and found myself unable to find a suitable reason to decline. 

Finally, a question.  'Tis the season to purchase some new machinery.  So is retina display for my next laptop a must-have, not worth it, or somewhere in between?  I'd appreciate opinions. 

Easy Now

In the past year or so, I've gotten reviews back on multiple papers with the complaint that the result was too simple.  My interpretation of review: sure you might have come up with an efficient data structure that solved an at least seemingly interesting and/or useful problem, but wasn't the underlying math and/or data structure approach "too easy"?  (The reviews were either from theory conferences or, my interpretation, from theoretically minded reviewers in settings where there might have been a mix on reviewers.)  I'll admit, it's a bit disheartening.  And I'll also acknowledge that blogging about it probably seems like sour grapes.  But here it goes.   

From my standpoint, easy is a plus, not a minus.  I've taken to describing it this way.  In computer science we're used to measuring algorithms and data structures in terms of the two basic tradeoff costs -- time and space.  The third basic cost -- error -- takes some people a while to get used to.  That is, your algorithm can be "wrong" (either probabilistically, or in that it gives an approximate answer) in some hopefully well-defined way in order to trade off against time and space needs -- many times you're willing to settle for a good answer instead of the optimal answer if it's much quicker.  But there's also a 4th basic tradeoff cost -- programmer time -- that I find the theory community is happy to just ignore.  Simple is good, because more people will use simple things, even if they're not the most efficient possible, because often the usual time/space efficiency isn't really the bottleneck.  Coding up something that works is.  This is why Bloom filters show up in most of my talks (Suresh, drink!);  for me they provide an outstanding example of issues related to the 3rd and 4th tradeoff costs.

But I was inspired to go ahead and post something about this because of the following from Paul Krugman's blog today.  (His title is "The Power of Two" -- if that's not a sign, what is?)  I figured he says it (everything?) better than I could, though you'll have to substitute CS keywords for economics keywords in the below.  

If this strikes you as too easy, and you think that real economics should involve harder math, well, I feel sorry for you — you just don’t get what it’s all about. (You’re what Rudi Dornbusch used to call a “fearful plumber”). And by the way, coming up with a really simple formulation of what seems at first like a very hard problem can take a lot of work. It sure did in the case of the MF lecture, where I actually did start with a really ugly saddle-path thingie until I realized that formulating the sudden stop the right way would make all of that go away.

Simple doesn’t mean stupid. Thinking that it does, does.

     

Visiting UC Davis

Before returning home last week I spent a day at UC Davis giving a talk.  I got the spend the day talking to various people I've collaborated with there (like Raissa D'Souza, Nina Amenta, and John Owens), and enjoyed getting to see and talk with Charles (Chip) Martel, who when he's not busy as a computer science professor is busy being a world championship bridge player.  I spent several nights up late last month watching him play (via bridge's version of an Internet broadcast) online in the world championships in Bali. 

The big news was that Davis looks to be hiring this year, and one of the areas might be some variation of "big data", with theoretical types definitely included that category.  Davis is nicely located about an hour's drive north of Berkeley (in reasonable traffic), and enjoys standard California amenities.  (The day there was filled with ridiculously nice weather and excellent food.)  If you're job searching, you should look for their job announcement.

Mitzenmacher Drinking Game?

I've been visiting the Simons Institute for one of their workshops the last few days.  I got my advisor Alistair Sinclair to give me a tour.  I have to say, that's an amazing space they have.  A very nice building, and they've set it up wonderfully (lots of light and open working spaces).  I can't believe their location on the Berkeley campus. 

After my talk, someone told me (and now I forget who) that someone (Michael Goodrich?) said that the Mitzenmacher talk drinking game was that you took a drink every time a slide says "Bloom" or "cuckoo".  That would be a dangerous drinking game.  (It's funny because it's true.)

NSF Coming Back Online

I was impressed how quickly the NSF got Fastlane back online.  (I think it was turned on a few hours after the shutdown was ended.)  But like many people, I'm awaiting to hear how the missed deadlines (or upcoming deadlines) will be manged.  I haven't seen word on that on the web site, but looking online I found this article.  It suggests that "BFA will establish and publish on the NSF website within one week agency-wide policies for proposal deadline extensions and other grant-related actions."  (I am not sure what the BFA is.)  That pretty much matches my expectations.  I can imagine it's very difficult catching up after being shut out of your office for two weeks, especially when having to deal with the concerns of hundreds/thousands of scientists who want to find out what's going on.  I'm not at all surprised that they have to take several days to figure out what the best way forward is.  Heck, it probably will take several days just to catch up with the weeks of e-mail and other paperwork. 

I think the article is encouraging patience on our part.  If you're awaiting word, just check into the NSF web site this week.  If you see or hear anything important, try to help spread the word.  The NSF has, in my experience, been very reasonable about dealing with things, and I'm sure they're working to figure out a way forward that is effective and fair to the people waiting to turn in proposals or otherwise participate in NSF activities.

Simons Research Fellowships Post

Alistair Sinclair asked me to post a note about the Simons Research Fellowships positions at Berkeley.  But since that's where Justin Thaler (my now-ex student) ended up, I thought he could put in a few words about his experience to add a personal effect.  Justin says...

Having been a Research Fellow at the Simons Institute for a couple of months now, I cannot speak highly enough about the experience. Others have already given a sense of how exciting it is to be here, so I'll just briefly list some of the things I find most striking about the place.

* The atmosphere is surprisingly collaborative, even for a place specifically designed to foster collaboration.
* Any time I have a question I can't answer, there is an expert's door I can immediately knock on.
* There's a great mix of junior and senior people.
* It's particularly fun hanging out with other Research Fellows! And I look forward to every Friday, when we all meet for lunch and one of us gives a short, informal talk on, well, whatever that person wants to talk about.
* Seriously, what's not to like about having no non-research responsibilities, surrounded by dozens of top researchers in the same boat?

With that very positive description, here's the formal information:

================================================================

The Simons Institute for the Theory of Computing at UC Berkeley invites applications for Research Fellowships for academic year 2014-15.

Simons-Berkeley Research Fellowships are an opportunity for outstanding junior scientists (up to 6 years from PhD by Fall 2014) to spend one or two semesters at the Institute in connection with one or more of its programs.  The programs for 2014-15 are as follows:

* Algorithmic Spectral Graph Theory (Fall 2014)
* Algorithms and Complexity in Algebraic Geometry (Fall 2014)
* Information Theory (Spring 2015)

Applicants who already hold junior faculty or postdoctoral positions are welcome to apply. In particular, applicants who hold, or expect to hold, postdoctoral appointments at other institutions are encouraged to apply to spend one semester as a Simons-Berkeley Fellow subject to the approval of the postdoctoral institution.

Further details and application instructions can be found at http://simons.berkeley.edu/fellows2014.  Information about the Institute and the above programs can be found at http://simons.berkeley.edu.

Deadline for applications: 15 December, 2013.

Some Advice on Entrepreneurship from the AH meeting

At the Andreessen Horowitz academic round table (see past post), there was various advice, some of it contradictory, for professor-types interested in starting companies.  I should start by saying that all of this is my interpretation of the advice, and the various people involved are not responsible if I've gotten it wrong.  Certainly further opinions are welcome.  

At the research level, Nick McKeown expressed some of his rules for research projects.

1. Pick a problem that is intellectually interesting.
2. And improves the practice.
3. And industry doesn't like (yet).

His idea (my interpretation!) was that if industry liked the idea, then the problem wasn't out there enough in terms of a time horizon.  Also, given the resources in industry, if industry really liked an idea, they could throw more resources at it than researchers at a university.  This idea had some pushback.  For example, Michael Franklin said the AMPLab at Berkeley had a lot of enthusiasm from industry, and that the industry support and interest was very positive in terms of their success.  (AH very recently funded a startup that came out of the AMPLab.  And the AMPLab is very impressive in terms of its resources, including people -- lots of great faculty.)

I will say that part of Nick's conception resonated with me.  When I've expanded my research into new areas, I've found at times that people in that area can be very negative.  And when that happens, it often turns out to be the most interesting research.  The work on low-density parity-check codes from way back when was roundly criticized by multiple old-guard coding theorists when we first presented it, and then suddenly there were entire sessions at coding theory conferences on the subject.  If you're inspiring angry reactions, you may indeed be on to something in your research.  (Of course, as he also acknowledged, you may also just be wrong.)

Another key issue that arose was "commitment".  The VCs at AH expressed some skepticism for professors who wanted to take a year (or maybe two) off to help set up a company but then hand it off and go back to their regular job.  Besides investing in an idea, they're investing in a team, and it's not a great sign if the team leader isn't committed.  Also, there's the feeling that that sort of change in leadership can have a huge transition cost.  (Also, I think, as I mentioned previously, they really seem to like working with tech CEO's.  Handing a company off may remove the "tech" leadership.)  They were fine with a model where it was professors and graduate students starting a company, and the commitment was coming from the graduate students;  in that case, a "part-time" professor founder could be workable.

I personally think the "commitment" issue can be a challenge.  It's a problem for me, with liking my regular job so much.

There was various talk about patents.  Most of the crowd were against making them a priority in starting a business, and recommended not getting them.  A patent, it is said, is just a license to sue, and who needs or even wants a license to sue?  Making your work open-source to get excitement and interest, and then commercialize after that point, can be a very successful business model, and maintains the academic desire to get the basic work out to a wide audience.  But perhaps most importantly, as an academic, patenting your work means dealing with your school's version of the Technology Licensing Office, and nobody says anything good about their Technology licensing offices.  (Even the west coast schools -- the best anyone said is that generally theirs would stay out of your way.)  A patent gives your TLO license to ask for whatever percentage of your soon-to-be company they feel like asking for, and until they sign off, it can be hard to get a VC interested in a company where another entity holds the patent.  And generally speaking, your success is not their performance metric.

(Two quick additional points related to TLOs.  Many noted that most TLOs have been brought up by the medical school/biology groups in the university, where patents matter a lot and licensing is a strong way to go.  That's much less so in CS tech.  Also, while you'd think TLOs would be thrilled to have professors/graduate students start companies, get very wealthy, and donate back to the university -- that doesn't seem to be their model, as enlightened as it might seem to us.)  

I certainly know some cases where patents at least seem to me to have been important to "startup" companies.  (Akamai/Limelight?)    But the rest of what was said seemed to make a lot of sense.   

One thing the VCs emphasized is the importance of timing.  They said the idea behind many startups had actually been around for a while, the subject of study in universities or labs, but often the timing has to be right to make the move into the product space.  Sometimes other technology has to catch up, or something else in the environment has to go your way.  A lot of "failures" may not be failures of the idea, but just not the right timing.  

It was expressed that startups that have a mission to change the world in some interesting way were better off than startups whose mission was just to make money.  In particular, it can help recruit the best and the brightest, creating a very powerful positive feedback loop.  Simply stated missions -- Google says theirs is to "organize the world's information and make it universally accessible and useful" -- can be quite powerful.  The cynical might question people's motivations and whether money is really what's behind the mission, but either way, missions can be useful.

Finally, and perhaps this isn't so surprising, but the best way to connect with VCs is probably through personal connections.  If you know someone that's worked with the VCs, get them to introduce you.  The VCs apparently get thousands of proposals sent to them a year, and very few of those get consideration.  Having someone they trust vouch for you means a lot in terms of them being willing to make time to listen to you.  That's not unlike aspects of academia (the importance of letters for jobs/graduate school;  in some cases connections being helpful for getting funding from industry).  While not surprising, it seems worth saying. 

Entrepreneurship and the Curriculum

At the Andreessen Horowitz academic round table (see last post), the issue of how to promote student entrepreneurship through the curriculum arose.  The VCs at AH (which I'll use for short hereon) want there to be more tech-based CEOs.  As they put it, it's easier to teach a tech person what they need to learn about business than to teach a business person what they need to learn about the tech.  Somehow, in most universities and I believe in the world at large, the culture has developed that the business people think they're the powerful ones, not the tech people who build the things that consumers love.  The business people think they're the ones delivering the value, and then divide the value accordingly.

Don't believe me?  Go see http://whartoniteseekscodemonkey.tumblr.com/ , a site (that came up in the discussions) devoted to the e-mails sent by Wharton business school people looking to hire (undergraduate) programming and engineering talent.  As a faculty member I get bunches of these sorts of e-mails a month, and I'm sure the computer science students do as well.  The underlying message is that the tech people are commodity cogs to be plugged in as needed.  That's not the message we want our students to get, and not how things really work in most successful startups.  

So AH says they believe in and support the tech CEO, and want to encourage that.  What does that, and entrepreneurship generally, mean for our curriculum?  Should CS departments have courses on entrepreneurship (or give credit for classes in other departments on the subject)?  Should we teach computer languages that are the latest on the start-up scene (in preference to those that, arguably, provide a larger conceptual framework or encourage certain ways of thinking)?  Should we have an "entrepreneur track", like we might have a theory track or AI track or computer science and engineering track?  What is the school's role at the department's role in encouraging entrepreneurship?  Some people thought CS departments perceive themselves as professors in the business to make more professors, and thereby ignore the potential CS has to change the world via business.

These are tough questions.  One issue that makes it even more problematic for CS is that these problems are not faced by many other parts of the university -- literature, history, and even most of the social sciences don't have a significant start-up scene -- which means in some ways, we're on our own.  Indeed, significant parts of the university might actively resent an emphasis on entrepreneurship, which they might argue does not always fit so well with the university's educational mission.  (Or,  perhaps, it just represents self-interest on their part.)

Aged fuddy-duddy that I am, I'm somewhat sympathetic to this view.  Computer science is science.  I want to educate students about the great questions (and answers) of computer science, and I am thrilled to be educating the next generation of scientists, especially computer science.  But yes, computer science is also engineering (in the practical sense of the word), providing the ability to solve immediate problems, yielding economic benefits to the users and of course the developers of the solutions.  I see striking the right balance as a challenge;  greedily, I do somehow want both.

At Harvard, I feel we've been pushed and pushed ourselves to make the requirements for the major quite minimal (in terms of the number of classes), so I want those required classes to be on the "science" side.  I want computer science graduates to have both breadth and depth in computer science.  Much of the entrepreneurship can naturally fall outside the curriculum -- there are now a number of student organizations, and university-level initiatives, to promote entrepreneurship.  (Harvard, I think, has been finding a way to expand the concept of entrepreneurship beyond just "business" -- into the larger concept of innovation -- to make it more appealing throughout the university.  For example, check out the i-lab.)  At the same time, I'm clear that having all the entrepreneurship activities fall outside the traditional curriculum potentially pushes a set of students away.  Again, we're left with finding the right balance, for us.

Sadly, the meeting's discussion on this only lasted a short while, and I felt left with more questions than answers.  Feel free to discuss your thoughts here.