France excels at R&D, but Academia is overdue for disruption(rudebaguette.com)
rudebaguette.com
France excels at R&D, but Academia is overdue for disruption
http://www.rudebaguette.com/2012/05/09/r-and-d/?utm_source=hackernews&utm_campaign=hackernews
9 comments
Agreed. Besides the length issue of a tweet (which don't apply to blog posts, as we all know from Steve Yegge) I also think that there is no incentive for a researcher to participate in the social web--at least none that I can think of. Actually, quite the contrary is true: yesterday's post on academic blogs linked to the "serious engineering" blog, which contains the following line in a post about time management:
Do not read blogs and above all do not write them.
I'm fairly sure that line from Anthony Finkelstein is tongue-in-cheek.
Like any profession, academia is about networking. Social media can really help here, and I think academics are slowly understanding this. There are two problems: blogging/tweeting are lower priority than grant-writing, teaching, marking, and paper-writing; and academics are usually older and (in my experience) older people don't 'do' social media as much.
But in software engineering, at least, there is a good community of people on social media. For example, the Never Work In Theory blog (of which I'm an author), and various academics on twitter, like @profserious or @avandeursen.
Like any profession, academia is about networking. Social media can really help here, and I think academics are slowly understanding this. There are two problems: blogging/tweeting are lower priority than grant-writing, teaching, marking, and paper-writing; and academics are usually older and (in my experience) older people don't 'do' social media as much.
But in software engineering, at least, there is a good community of people on social media. For example, the Never Work In Theory blog (of which I'm an author), and various academics on twitter, like @profserious or @avandeursen.
As someone tangentially involved in the administration apparatus for large, well utilized clusters, I have to dispel some myths related to "Cloud" services and Amazon EC2 for computation. First, if your school has institutional cluster services, these are FAR cheaper than cloud options. Secondly, the type of systems that are good for scientific computation are not the type of boxes typically deployed in the cloud; try to find a 48 terabyte memory node in the cloud.
OSG/Teragrid are much better options than the cloud, though you do have to jump through some hoops to access them. Believe me when I say it is worth it though.
OSG/Teragrid are much better options than the cloud, though you do have to jump through some hoops to access them. Believe me when I say it is worth it though.
Definitely agree. To give a ballpark figure, Compute Canada, the governing HPC body in Canada provided a cost estimate to researchers who applied and received dedicated computer allocation. Although, all this computer time is actually "free" to the scientist:
"The average RAC award in 2012 was 500 core years and 50 TB years. From Penguin Computing's website [list pricing from Feb 10th, 2012] the cost to purchase a similar amount of computational time and ability would be $450,000. ($600 / server month where each server provides 8 cores) To purchase 50 TB from SDSC [again, list pricing from Feb 10th, 2012] it would cost $30,000. ($600 / TB Year) Making the total value of the average RAC award nearly $500,000. The cost to Compute Canada to provide this level of award is $178,000 and that includes all aspects of user support, training and other aspects not covered by commercial clouds." (https://computecanada.ca/index.php/en/component/content/arti...)
As a side-note, my groups award was above the average, The email to our research group stated: "Providing these resources to your research group costs Compute Canada roughly $4,669,960." I don't even want to calculate how much that would cost on EC2!
"The average RAC award in 2012 was 500 core years and 50 TB years. From Penguin Computing's website [list pricing from Feb 10th, 2012] the cost to purchase a similar amount of computational time and ability would be $450,000. ($600 / server month where each server provides 8 cores) To purchase 50 TB from SDSC [again, list pricing from Feb 10th, 2012] it would cost $30,000. ($600 / TB Year) Making the total value of the average RAC award nearly $500,000. The cost to Compute Canada to provide this level of award is $178,000 and that includes all aspects of user support, training and other aspects not covered by commercial clouds." (https://computecanada.ca/index.php/en/component/content/arti...)
As a side-note, my groups award was above the average, The email to our research group stated: "Providing these resources to your research group costs Compute Canada roughly $4,669,960." I don't even want to calculate how much that would cost on EC2!
500 cores is approximately 32 cc2.8xlarge instances (16 cores/instance). If you are running a highly utilized cluster, i.e. you are going for a one year heavy utilization reserved instance, the compute part is going to cost you ~$262,000. If you went with a 3-yr RI, it would be $183,000/yr.
Or to put it differently, ~$0.04/core-hr prior to any volume discounts.
Or to put it differently, ~$0.04/core-hr prior to any volume discounts.
Absolutely. Also, while the article may be right that a lot of research-group clusters being run out of a closet are only getting 10% utilization, this is not true for shared institutional clusters. Those systems are often hitting utilization of 70, 80, or 90%, and are a lot more cost-effective than a cloud provider.
This is why a lot of institutions request that money spent on new compute hardware be contributed to the shared system (in exchange for a large allocation), rather than building tons of tiny clusters.
This is why a lot of institutions request that money spent on new compute hardware be contributed to the shared system (in exchange for a large allocation), rather than building tons of tiny clusters.
The argument about France's strength at the end of the article is anecdotal (and not argued at all), and the title is misleading.
(and as a French CS student who did his undergrad in France and started a PhD in the US (and have many friends in PhD tracks in both systems), I'd actually argue that France is better at "pure/abstract research" rather than R&D. Inria is a very unusual organization, not representative of research in France at all)
(and as a French CS student who did his undergrad in France and started a PhD in the US (and have many friends in PhD tracks in both systems), I'd actually argue that France is better at "pure/abstract research" rather than R&D. Inria is a very unusual organization, not representative of research in France at all)
Some data: Inria is (AFAIK) one of the 3 major public research institutions in France: CNRS (the largest, multiple scientific fields, 26k people), Inria (CS, 4k people), INSERM (Medical, 6k people). There are others, but they are much less staffed. Anecdotally, I worked in a CNRS lab and I can tell you that it was very much applied. But applied research was the stated goal of the lab, and I can't say about the rest of the CNRS.
You forgot CEA (nuclear and renewable energy, microelectronics, defense,... 16k people).
You are right but it seems that the CEA is an établissement public à caractère industriel, while the ones I cite are établissements publics à caractère scientifique.
However, you are right, this distinction seems pretty arbitrary to me, as the ONERA (aerospace) too is classified as "industrial" and not "scientific" research establishment.
However, you are right, this distinction seems pretty arbitrary to me, as the ONERA (aerospace) too is classified as "industrial" and not "scientific" research establishment.
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I think this post misses a number of things. For example, take peer review. The system is not perfect--but peer review takes time and expertise. It's not as simple as a "like". When I review an article--I check for consistency. If necessary, I go through the references. At times, I make sure that errors have been propagated correctly. Then, there are broader issues such as relevance. In short, it's labor intensive and sometimes there are bad referees--but overall, I think the system is better than a simple comment system. In modern terms, you might call it "curated" content--the referees and editors help increase the signal to noise ratio in the sea of papers that are submitted.
For conferences--while the presentations are important, so are the conversations in the halls, at dinner, etc. It's useful to have face to face conversations with your collaborators and to make new ones.
There have been some changes--like for initial program committee meetings for conferences sometimes take place using webex/gotomeeting given the diverse timezones/countries of members. Some experimentation has been done with using second life for the first stage of grant reviews--but at the end, physical meetings are necessary. For conferences themselves (in physics), you are paying on average less than $1000--even for conferences with ~10,000 people. But--conferences do cost money to organize--I made a mistake for the first workshop I organized by charging too little...
Things are gradually improving--slides from the invited talks are hosted online for the major conference from my field. Mobile schedules could be improved...
Others have commented on the EC2 question--but one other thing to consider is whether their architecture is suited to a given problem. We're investigating this now.
While Hadoop is good for some problems, it may not be appropriate for others. This is generally true of a number of the points in the article--use the right tool for the right job--don't just use it because it is new...
For conferences--while the presentations are important, so are the conversations in the halls, at dinner, etc. It's useful to have face to face conversations with your collaborators and to make new ones.
There have been some changes--like for initial program committee meetings for conferences sometimes take place using webex/gotomeeting given the diverse timezones/countries of members. Some experimentation has been done with using second life for the first stage of grant reviews--but at the end, physical meetings are necessary. For conferences themselves (in physics), you are paying on average less than $1000--even for conferences with ~10,000 people. But--conferences do cost money to organize--I made a mistake for the first workshop I organized by charging too little...
Things are gradually improving--slides from the invited talks are hosted online for the major conference from my field. Mobile schedules could be improved...
Others have commented on the EC2 question--but one other thing to consider is whether their architecture is suited to a given problem. We're investigating this now.
While Hadoop is good for some problems, it may not be appropriate for others. This is generally true of a number of the points in the article--use the right tool for the right job--don't just use it because it is new...
There actually is a really strong community of mathematicians at mathoverflow.net. Also, I know quite a few academics who tweet about their research but these are definitely the exception rather than the norm.
A simple reason as to why academics aren't "socially connected" is that they don't need to be. The academic social network exists informally and is more tightly knit than a social network of say programmers, so I don't necessarily have to be your facebook friend or follow you on twitter to be able to get in touch with you through 2-3 hops
As far as blogs are concerned, one reason to write blogs is for purely didactic purposes. I definitely know tons of Grad students who use to prepare their notes and put them on their web pages or local servers to fulfill that need. The other reason: To transmit your ideas to wider audience is much a more harder problem to solve. Mathematical abstractions get progressively harder to communicate if your understanding of the basics is weak, example, you would definitely need a background in vector spaces to understand functional analysis. I remember reading a blog recently where the author ( a machine learning academic) had written about his experience in implementing a stochastic gradient solver for online learning in Clojure: There were a couple of comments complaining that there was no context. While, I definitely see where those folks are coming from, it would take too long and a good deal more posts to be able to break down a couple of book's worth of ideas before you get to what you want to talk about.
A simple reason as to why academics aren't "socially connected" is that they don't need to be. The academic social network exists informally and is more tightly knit than a social network of say programmers, so I don't necessarily have to be your facebook friend or follow you on twitter to be able to get in touch with you through 2-3 hops
As far as blogs are concerned, one reason to write blogs is for purely didactic purposes. I definitely know tons of Grad students who use to prepare their notes and put them on their web pages or local servers to fulfill that need. The other reason: To transmit your ideas to wider audience is much a more harder problem to solve. Mathematical abstractions get progressively harder to communicate if your understanding of the basics is weak, example, you would definitely need a background in vector spaces to understand functional analysis. I remember reading a blog recently where the author ( a machine learning academic) had written about his experience in implementing a stochastic gradient solver for online learning in Clojure: There were a couple of comments complaining that there was no context. While, I definitely see where those folks are coming from, it would take too long and a good deal more posts to be able to break down a couple of book's worth of ideas before you get to what you want to talk about.
Reading and writing tweets is a pleasant time-waster that should be seriously limited if you want to achieve something serious, not encouraged. The same applies also to HN, of course, where I am now wasting time to avoid research :P
There are enough (and too much) scientific stuff to read in any interesting, active research topic; the bottleneck is in the researcher's ability to read and understand, not in lack of content.
And even peer reviewed articles in respectable publications quite often are garbage and/or wrong. If your proposal "let's do stuff this way" isn't even peer reviewed, then it's most likely not worth reading - since there's a too high chance that it's one of:
a) duplicate of something that was already done in 1970'ies by someone else, and abandoned as it's not practical in real life due to X,Y and Z that you haven't considered yet; b) misleading or simply not true, as it's not researched / repeated / analyzed enough; c) Simply useless.
After all, if it was correct, novel and interesting, then there are quite a lot incentives for putting it to 'traditional' publishing; so if you're not publishing it 'properly' then it's an indication that you are doing it because your content is not publish-worthy, as people tend to squeeze as much publications as they can out of any decent, publish-worthy research.
There are enough (and too much) scientific stuff to read in any interesting, active research topic; the bottleneck is in the researcher's ability to read and understand, not in lack of content.
And even peer reviewed articles in respectable publications quite often are garbage and/or wrong. If your proposal "let's do stuff this way" isn't even peer reviewed, then it's most likely not worth reading - since there's a too high chance that it's one of:
a) duplicate of something that was already done in 1970'ies by someone else, and abandoned as it's not practical in real life due to X,Y and Z that you haven't considered yet; b) misleading or simply not true, as it's not researched / repeated / analyzed enough; c) Simply useless.
After all, if it was correct, novel and interesting, then there are quite a lot incentives for putting it to 'traditional' publishing; so if you're not publishing it 'properly' then it's an indication that you are doing it because your content is not publish-worthy, as people tend to squeeze as much publications as they can out of any decent, publish-worthy research.
Actually, call me a twitter-blase, but I'm not so excited and upbeat about Twitter anymore. The fact that people tweet stuff during a presentation don't get me excited. I'd rather they listen and learn from the presenter. Then I can say mission accomplished (as a conference organizer).
I just know too many great people who don't spend any time on Twitter, and frankly, why should they? I see a lot of self-promotion, "social media" experts retweeting to death. Real people saying interesting things? Some, but not enough to keep me engaged.
I just know too many great people who don't spend any time on Twitter, and frankly, why should they? I see a lot of self-promotion, "social media" experts retweeting to death. Real people saying interesting things? Some, but not enough to keep me engaged.
I dread the day that scientists try to condense their research into 140 characters. Reading well thought out blog posts would be great, but to be honest, the ideal would simply making it easier for me to find out what the best papers are.
I always assumed that scientists generally do not participate in the wider web as much due to having much faster academic links than the average net user could even dream of.
However, that said, there are many things that can be improved upon that the wider web would be great for. Academic publishing is one obvious one and the Elsevier boycott is a strong indication that this is well underway.
Data collection and sensing is another, which with the new class of cheap networked devices like the Rasperry Pi, as well as pads and smartphones, could well be something that is worth putting some thought into.
Distributed computing and mass collaboration is another obvious one, however it seems that academics can often get this more or less for free, if you look at examples like folding@home and the NASA moon crater identification project thingy, so there might not be so much requirement for things like EC2 or mechanical turk, when compared to getting people to donate resources for nothing.
However, that said, there are many things that can be improved upon that the wider web would be great for. Academic publishing is one obvious one and the Elsevier boycott is a strong indication that this is well underway.
Data collection and sensing is another, which with the new class of cheap networked devices like the Rasperry Pi, as well as pads and smartphones, could well be something that is worth putting some thought into.
Distributed computing and mass collaboration is another obvious one, however it seems that academics can often get this more or less for free, if you look at examples like folding@home and the NASA moon crater identification project thingy, so there might not be so much requirement for things like EC2 or mechanical turk, when compared to getting people to donate resources for nothing.
And of course, most research isn't particularly interesting to people outside a fairly small area. I might come up with a new way of doing something important in my research area 50 times faster than we did it before, but explaining what I did struggles to fit in 15 pages, never mind 140 characters. Personally I can't imagine what interesting research related-comment you could fit in a tweet. Then again, I've never got twitter (which isn't something I'm proud of -- sufficiently many people are using it that I am sure I'm missing something.. just not sure what).