11 ms·

A Funny Thing Happened on the Way to Academia

209 points by tim_sw 14y ago

aria 14y ago
I'm the post author and would be happy to answer any questions and discuss academia CS and startups.
- mikedmiked 14y ago
  How does prismatic actually use NLP for finding articles you like? Does it use sentiment analysis of reviews from people it thinks are similar to you? Btw I think "subreddits on steroids" is an incredible testimonial catchphrase - it would have been enough for me to buy your app, but I don't own a smartphone.
  - aria 14y ago
    I recently answered a Quora question about this that has many more details http://qr.ae/1viyQ http://qr.ae/1viyQ. The core NLP behind Prismatic is topic modeling; we don't use anything off the shelf, but something crafted pretty specifically to our needs. We do model user similarity based upon interest overlap and social graph analysis. So we know how likely you are to care about what someone in your extended network shares.
    - _delirium 14y ago
      Do you plan to publish the algorithm/model at some point, or is it too closely connected to the business's "secret sauce"? The latter would be perfectly understandable, so not meant to be a hostile question, more curiosity out of personal interest of how you handle that aspect of private-sector research. Worries about that are part of what keeps me personally from jumping from academia. I'd like to do less paper-writing and more applied work, which fits nicely, but I'd still want to do some paper-writing and be able to discuss techniques publicly, which seems to fit more awkwardly. I assume it's possible to pull off both, but all the people I know who've left academia for startups have stopped publishing completely, and many of them doing ML/big-data stuff are quite secretive about their techniques.
      - aria 14y ago
        We will publish on interesting aspects of our models. Frankly, our main reason for not doing so is time and resources. In terms of industry research on the whole and publishing. It is true that you can't publish everything, but look at Google. Arguably some of the influential systems papers of the last decade or so have come out of Google. Google doesn't publish all the details of their search algorithms, but it turns out that because they address real-world problems they've done enough great stuff that some of it can safely be shared without endangering their moat. Another aspect to consider is that while industry publishes less, we do tend to churn out useful open-sourced (Prismatic will definitely be doing that soon) that is of at least comprable utility to people out there as most papers.
        Evbn 14y ago
        Has academia published any relevant systems papers since 2007?
        _delirium 14y ago
        Hard to say: systems has a long lag time before good ideas get "proven" good by being successes in the marketplace. For example, paravirtualization was investigated from around 2000, and then Cambridge released Xen in 2003. It caught on by the end of the decade, in the late 2000s. If something released in 2010 will end up having similar impact, we'll know it by the late 2010s...
      - deleted 14y ago
        [deleted]
- temphn 14y ago
  Great article, and agreed on most everything you said. Regarding Prismatic itself, some constructive feedback (feel free to ignore). My immediate first impression was that this was another app that would waste my time. I want less of those, not more. The absolute best news feed app I've used is Flipboard for the iPad, and even then I don't use it too much as I feel too much like I'm wasting time with it (like HN!). Secondarily, the homepage doesn't grab you enough. The text in the graphics is too blurry and the pictures are generic. The homepage below the icons doesn't have the production values to explain why it's cool. I'm not trying to be negative here. Some of the points in your article really hit home (email summarization would be awesome and paradigm shifting). So I wonder if you might focus more on making something that will save people time and solve a pain point vs. "another web-based time-wasting thing" (that may not be fair, but that was a first impression). For example, can you scrape an inbox and list of Facebook/Github/Tumblr/RSS/Twitter feeds to get a single high-sensitivity greatest hits from all monitored news feeds? This way you can check a single page in five minutes on your phone and feel reasonably content that you saw the top headlines for that week. Kind of like news.ycombinator.com/best. Just some thoughts, FWIW.
  - deleted 14y ago
    [deleted]
  - robrenaud 14y ago
    > For example, can you scrape an inbox and list of Facebook/Github/Tumblr/RSS/Twitter feeds to get a single high-sensitivity greatest hits from all monitored news feeds You've missed the point already. The web is vast, on the whole filled with 99.99% crap. But .01% of something large is still very big. You cannot list the interesting things a priori with a few feeds. Prismatic is about learning about what you actually like to read and giving it to you. It's got the smooth/sleak usability of Google reader (read title, keep smashing J when something isn't worth reading, essentially letting you skim/reject more than 10 uninteresting articles/minute), but without the low recall "enumerate every site I think I am interested in" subscription model. It's compelling and awesome.
    - temphn 14y ago
- rom16384 14y ago
  Hi. I'm trying use natural language generation (NLG) software, and found lots of long dead projects, two large lisp-based packages (FUF/SURGE, KMPL) that are not updated in years and not user friendly at all and a simple java package (SimpleNLG) that is indeed simple but not very sophisticated. Is this representative of the NLP/NLG software?
  - PeterisP 14y ago
    Controlled languages are interesting for natural language generation purposes - for example, GF (http://www.grammaticalframework.org/ http://www.grammaticalframework.org/) may be useful for building sentences (in multiple languages, if needed) from an abstract data structure.
    - rom16384 14y ago
      GF seems very interesting, thank you.
- pseut 14y ago
  Really interesting article, especially since I'm an assistant prof idly considering the same sort of move. How much of a "business model" did you have before commitment -- did you have enough connections that you were confident you'd get funding once you had the idea mapped out in detail? Was UMass still a viable safety net, or were you fully committed?
- HalcyonicStorm 14y ago
  Random, but I love that the name is a play on the amazing movie "A Funny Thing Happened On the Way to the Forum" +1
  - Evbn 14y ago
    It is a play on the name of the play.
- javajosh 14y ago
  Hi Aria. I have a question regarding the use of automatic sentiment analysis and it's relationship to choice. It seems to me that there is a fundamental divergence between the program of "give me what I will enjoy" and "give me what I need". It seems that your startup is focused entirely on the former question, and there's no doubt that if you are successful you will indeed be consuming more attention, which is of course the primary commodity in the attention economy. But wouldn't it be better to use NLP to emancipate people from the attention economy altogether, to help identify not what people want, but what they need to he happier, and more engaged in the real world doing real things for real people?
  - dxbydt 14y ago
    >But wouldn't it be better to use NLP to emancipate people from the attention economy altogether I work on ads recommendations, and yes, it would be "better" if I stop recommending KFC to the 36% of obese Americans & instead recommend Crossfit or Yoga or Gold Gym or Myoplex. If I do that, they will quit the site en-masse and the negative engagement rates will go through the roof, I'll be out of a job, will end up eating at McDonalds to save money, and then become obese, and then click on the same KFC coupon recommended by another data scientist hired to replace me :) Yes, it would be "better" if people read the Economist instead of Cosmo, or went to grad school instead of building crud web apps, or watched Frontline PBS instead of Jerry Springer, but then, it would also be much "better" for the environment if we got rid of the 1000s of walmarts & safeways selling groceries & Uncle Sam shipped you healthy lettuce and spinach weekly via USPS....communism 101 :)
    - javajosh 14y ago
      Sorry you got downvoted - wasn't me, I swear (it actually annoys me that people use downvoting to mean "I disagree".) The problem with your comment is that you present a false choice. I believe that there is strong - very strong - demand for real, lasting happiness. Indeed I think that is the strongest demand there is. NLP and technologies like it can be at the core of the tools that help people choose who they want to be and help (not coerce) them to act consistency with those choices.
- eternalban 14y ago
  - Do you think you would have the opportunity to avail yourself of the fruits of "academia" if the current approach was fundamentally broken? - What would happen if viability of academic research was tied to one being a successful business person? (Asking in light of your comment elsewhere in this page re. "tenure system".)
- nobody-special 14y ago
  what are you dancing to? http://cdn.getprismatic.com/cdn/img/people/aria-bio__60cac850.gif http://cdn.getprismatic.com/cdn/img/people/aria-bio__60cac85...
- carterschonwald 14y ago
  Loved your post. Very articulate and nicely written. I've been amidst the academia -> industrial fun transition myself this past year, absolutely best decision i've made in the past half decade. One point you only lightly touched on, but which I think is worth restating is this: in academia theres this frustrating sense of "if you're not narrow, you can't be deep", whereas I see a lot of the more sophisticated bits of industry really valuing folks who strive for broad depth. Would you agree with that assessment? (admission: i'm presently having a go at building some tech products/tools that tie into a whole range of my researchy interests)
iamtheneal 14y ago
Awesome post. I -- along with many of my colleagues from grad school -- have had pretty similar experiences with academia (minus the outlook for a promising academic career ;) ). This sort of thing (very smart people abandoning academia) is going to continue to happen unless academia figures out a way to make itself more relevant. academic |ˌakəˈdemik| adjective 2 not of practical relevance; of only theoretical interest : the debate has been largely academic.
- hyperbovine 14y ago
  My experience in academia thus far: for every five smart people abandoning academia for industry, one truly brilliant person remains behind. That's all that is required for the model to sustain. (And even then, there are not enough academic jobs to go around.)
junktest 14y ago
Zite too seems to be working in the same space of ML-aided personalized news magazines.
- mikeklaas 14y ago
  Several of us Zite employees are also refugees from academia, it turns out.
jamesjporter 14y ago
Great post. As someone who works in a different field of science, one bit got me thinking: >Like any academic community, the work within NLP had become largely an internal dialogue about approaches to problems the community had itself reified into importance. I would argue that this is an issue of goals. If you're motivated by the application of research results to solve practical problems (as the author is), then this is a valid criticism. But for me science is also self evidently valuable — understanding the principles that govern the universe is a noble goal irrespective of finding opportunities to apply them. Perhaps the field plays a role as well. In all sciences one's goal is to discover the rules and facts that govern a particular system. In the natural sciences, this system happens to be the world in which we live, whereas in the formal sciences (math / CS), the system is often an artificial one of human construction. In the natural sciences, the importance of the rules you discover is self evident (they govern our own lives and capabilities!), whereas in the formal sciences, its more necessary to justify the importance of your discoveries (with, say, practical applications) because the importance of the system you're studying isn't as self-evident. This isn't to say that the natural sciences are in some way superior; just a speculation about the attitudes/motivations of academics in different fields.
- iyulaev 14y ago
  In the natural sciences, this system happens to be the world in which we live Not to say I disagree with your post, but it's it more accurate to say that the natural sciences today explore models for the world in which we live? The models tend to be fairly obvious for things on the human scale, but when you talk about systems on the atomic scale, or on the cosmic scale, the immediacy of the models tends to break down. The result is that, just as for the abstract sciences (math, CS, etc), the usefulness of the models has to be justified. So, I feel that the line between purely abstract sciences and "natural sciences" is not quite as fine and well-defined as your post makes it to be.
  - tsewlliw 14y ago
    I really like knowing that there are people dedicated to thinking deep thoughts. There was a recent potential proof published on a tough math problem, and apparently the author had gone dark for 15 years creating a fantastic mathematical universe and vocabulary all on his own. Thats worthwhile. Maybe not for everyone to go off doing it, but definitely for some.
betula82 14y ago
Do you have ideas for how academia can be brought back into touch, or is it a lost cause?
- aria 14y ago
  Well, I think the number one thing that would correct the balance between academia and industry is if people could freely go from one to the other. Someone could take insights from one arena to the other, enriching both. There are many reasons why this is difficult, but the primary obstacle is the tenure system.
  - opminion 14y ago
    In the UK it is possible to switch between academia and industry, so long as you are satisfied with fixed term contracts in academia. Recruiters tend to get confused when someone turns at their doorstep with a PhD ("which marks did you get?"), and academics tend to not have a clue of what's the benefit of industrial experience (in spite of being effectively "agile" product managers themselves when participating in, say, a European Framework project).
deleted 14y ago
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sbashyal 14y ago
Having spent several years doing academic research before finally leaving to work on real-world problems in machine learning and NLP, I can relate to this article. If any of you have problems in this domain, I am interested to chat.
marshray 14y ago
A really fantastic article overall. I was never personally at risk of academia, so I don't resonate with that part of the article. But I particularly liked these two sentences for their practical insight: that process of taking qualitative ideas and struggling to represent them computationally is the core of artificial intelligence (AI). and that path from research to product rarely works, and when it does it's because a company is built with research at its core
- aria 14y ago
  Thanks! It seems like an obvious thing, but thinking about "operationalizing" intuitions computationally really helped me hone in on what I should be focusing on with research. My advisor Dan Klein was really awesome at teaching that.
deleted 14y ago
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HalcyonicStorm 14y ago
I love that the name is a play on the amazing movie "A Funny Thing Happened On the Way to the Forum" +1
galois198 14y ago
I was wondering, is it possible for individuals with no formal ML background to implement algorithms with as much subtlety as Prismatic?
- aria 14y ago
  Building Prismatic is way more than just about having a formal ML background. It's that along with large-scale systems skills and having a sixth sense for working with data (text especially) and knowing what simple ideas will work and what needs to be complicated. So to answer your question yes, you need a formal ML background but you need a lot else. Luckily, you can pick up all these skills from online courses, real world building, and a lot of self study and improvement
jacoblyles 14y ago
There are a lot of good ideas and sentiments in this article. And then at the end I find out the trail-blazing product he left academia for is "a newsfeed based on your interests." How many startups like this are there now? 300? That is probably a low estimate. I'm sure that everyone living in the Valley personally knows at least one founder working on the exact same product. And none of them are better than my Hacker News/ Facebook/ Reddit/ RSS feed combo. I've heard some of the many Prismatic competitors describe themselves as "a Pandora for news" which is an apt description, since rdio, soundcloud, and Spotify are better than Pandora. Self, social and community sourcing for digital entertainment tends to be better than algorithms. While I believe the "problem" domain is severely overworked, if you're going to stick with it then my bet is that social algorithms like collaborative filtering a la Netflix does a better job than topic modeling. On the optimistic side, a good company is more than a single product. Maybe the author's considerable expertise and experience from building Prismatic will lead to something cool down the road.
- xaa 14y ago
  My feelings exactly. It's made worse by the fact that, out of all the academic departments out there, AI and NLP research has perhaps the greatest potential to transform society in so many ways. He leaves the field trying to create intelligent machines in order to write a Google News clone? I truly don't get it.
  - IheartApplesDix 14y ago
    Then I don't think I can explain it to you. If you use HN and don't understand the impact of this work.. well there's a forest I'd like to show you. Amazon self publishing is just another publishing outlet. Google is just another index page. HN is just another alt.computer board.
    - stephengillie 14y ago
      To me, it feels like this person's talent is wasted on this project. With such a strong background in natural language processing, why isn't this person involved in a Siri competitor, in Web real time chat, VOIP compression, or AI speech? Is this the limited scope at which a typical CS Ph.D operates? Reach for the stars. Let people of lesser ability make news apps, even if it's a struggle for them.
yawgmoth 14y ago
I signed up to see how accurate it could be - the interests outlined in the e-mail I received seem pretty accurate but the stories that are being displayed have nothing to do with those topics. There was a dearth of interesting reading material.
zissou 14y ago
I faced a similar problem in academia, but it was in economics. I started my undergrad career as a computer science major, later ending up in economics, and I went on for my PhD in economics after finishing my BA. For those that aren't familiar, a PhD in economics is a lot like a PhD in mathematics. If you don't already respect economists mathematical ability, you really should, but that's not my point here because math is just a tool, and contains no absolute truths for the social scientist. In an effort to combine solid theoretical research with well built empirical models, I learned how to program Python to scrape data from web sites. Since nobody around me knew anything about computer science, I found myself having to teach myself everything when it came to "how would I write a program that collects X things from Y products in Z Internet markets". In the beginning, when I was learning to use Python libraries for doing HTTP requests (eventually converging to using 'requests'), how to parse that HTML (started with BeautifulSoup and then converged to 'lxml'), and how to aggregate and analyze that data (eventually converging to 'pandas'), I had to spend a lot of time learning the ins and outs of Python. To this day, I still think it was a great choice because Python has changed the way I approach any kind of business question that could be answered with a well defined empirical model. As a research assistant, I would spend 12 hours writing scripts to automate the collection and analysis of data for some project I discussed with a professor. The day after writing that script, I would go and talk to the professor and want to discuss some of the computational issues with the script (say, encoding issues, or even the use of computers on EC2 to help collect massive amounts of data every day), but the economics professors would not care at all to hear about any of that. "You need to be studying the economics, not the computer science" they'd tell me. This would infuriate me, because in my mind, if you wanted to be able to ask all these interesting questions that rely on the data, then you need to spend time to make sure you've done the computation correctly and in a way that is reliable. Maybe I dug my own grave by showing my excitement as I began to become more fluent with Python, and thus more confident in my abilities. Nonetheless, I eventually decided to leave my PhD program because my interests in topics that lie at the intersection of computer science and economics were a bad fit for my program. It was so disheartening to me because I truly loved economics, and was confident that what I intended to do with my PhD research was going to be unique and lay a framework for the field of industrial organization. However, the experience I received in my program was the lack of an adviser that could truly help me achieve what I wanted to do, and a regular negative response to anything I'd bring up that was out of the realm of what my professors were used to talking to graduate students about. Overall, as my tone may signal, graduate school has left me very, very bitter.
hna0002 14y ago
http://techcrunch.com/2012/12/05/prismatic/ http://techcrunch.com/2012/12/05/prismatic/
mitultiwari 14y ago
Nicely written blog! Agree with the author that academia sometimes focusses on a very narrow band of research topics, which might or might not improve end user experience. Also, agree with the author that personalized news has very interesting NLP+Machine Learning problems. However, I am not convinced that personalized news is what users wants, and whether users want to discover popular news and articles by serendipity, socially, rather than personalization by algorithms. Further, I think personalized news has very limited opportunity for generating significant revenue.
- jacoblyles 14y ago
  My suspicion about personalized news is that entrepreneurs are building things they know how to build rather than building something people want.
Irishsteve 14y ago
What exactly do people get out of all these news aggregators? I'd imagine the front page of reddit or at least alocalised version is more interesting than a personilised version. When does it go from news to infotainment? And if thats not the case why would someone think something beyond simple facebook like or twitter comment extractions is a big deal? I've seen lots of papers where representing a web page and a user in a vector space based on TFIDF performs well. I've even see Yahoo research post slides about using some form of random bucket for news recommendation because the novelty of newer / stranger articles improves ad click throughs. Then again did this article come out the same time as the PR release about funding for their company? If thats the case is this just a wide scale PR initiative?

209 points by tim_sw 14y ago

aria 14y ago

I'm the post author and would be happy to answer any questions and discuss academia CS and startups.

mikedmiked 14y ago
How does prismatic actually use NLP for finding articles you like? Does it use sentiment analysis of reviews from people it thinks are similar to you? Btw I think "subreddits on steroids" is an incredible testimonial catchphrase - it would have been enough for me to buy your app, but I don't own a smartphone.
- aria 14y ago
  I recently answered a Quora question about this that has many more details http://qr.ae/1viyQ http://qr.ae/1viyQ. The core NLP behind Prismatic is topic modeling; we don't use anything off the shelf, but something crafted pretty specifically to our needs. We do model user similarity based upon interest overlap and social graph analysis. So we know how likely you are to care about what someone in your extended network shares.
  - _delirium 14y ago
    Do you plan to publish the algorithm/model at some point, or is it too closely connected to the business's "secret sauce"? The latter would be perfectly understandable, so not meant to be a hostile question, more curiosity out of personal interest of how you handle that aspect of private-sector research. Worries about that are part of what keeps me personally from jumping from academia. I'd like to do less paper-writing and more applied work, which fits nicely, but I'd still want to do some paper-writing and be able to discuss techniques publicly, which seems to fit more awkwardly. I assume it's possible to pull off both, but all the people I know who've left academia for startups have stopped publishing completely, and many of them doing ML/big-data stuff are quite secretive about their techniques.
    - aria 14y ago
      We will publish on interesting aspects of our models. Frankly, our main reason for not doing so is time and resources. In terms of industry research on the whole and publishing. It is true that you can't publish everything, but look at Google. Arguably some of the influential systems papers of the last decade or so have come out of Google. Google doesn't publish all the details of their search algorithms, but it turns out that because they address real-world problems they've done enough great stuff that some of it can safely be shared without endangering their moat. Another aspect to consider is that while industry publishes less, we do tend to churn out useful open-sourced (Prismatic will definitely be doing that soon) that is of at least comprable utility to people out there as most papers.
      - Evbn 14y ago
        Has academia published any relevant systems papers since 2007?
        _delirium 14y ago
        Hard to say: systems has a long lag time before good ideas get "proven" good by being successes in the marketplace. For example, paravirtualization was investigated from around 2000, and then Cambridge released Xen in 2003. It caught on by the end of the decade, in the late 2000s. If something released in 2010 will end up having similar impact, we'll know it by the late 2010s...
    - deleted 14y ago
      [deleted]
temphn 14y ago
Great article, and agreed on most everything you said. Regarding Prismatic itself, some constructive feedback (feel free to ignore). My immediate first impression was that this was another app that would waste my time. I want less of those, not more. The absolute best news feed app I've used is Flipboard for the iPad, and even then I don't use it too much as I feel too much like I'm wasting time with it (like HN!). Secondarily, the homepage doesn't grab you enough. The text in the graphics is too blurry and the pictures are generic. The homepage below the icons doesn't have the production values to explain why it's cool. I'm not trying to be negative here. Some of the points in your article really hit home (email summarization would be awesome and paradigm shifting). So I wonder if you might focus more on making something that will save people time and solve a pain point vs. "another web-based time-wasting thing" (that may not be fair, but that was a first impression). For example, can you scrape an inbox and list of Facebook/Github/Tumblr/RSS/Twitter feeds to get a single high-sensitivity greatest hits from all monitored news feeds? This way you can check a single page in five minutes on your phone and feel reasonably content that you saw the top headlines for that week. Kind of like news.ycombinator.com/best. Just some thoughts, FWIW.
- deleted 14y ago
  [deleted]
- robrenaud 14y ago
  > For example, can you scrape an inbox and list of Facebook/Github/Tumblr/RSS/Twitter feeds to get a single high-sensitivity greatest hits from all monitored news feeds You've missed the point already. The web is vast, on the whole filled with 99.99% crap. But .01% of something large is still very big. You cannot list the interesting things a priori with a few feeds. Prismatic is about learning about what you actually like to read and giving it to you. It's got the smooth/sleak usability of Google reader (read title, keep smashing J when something isn't worth reading, essentially letting you skim/reject more than 10 uninteresting articles/minute), but without the low recall "enumerate every site I think I am interested in" subscription model. It's compelling and awesome.
  - temphn 14y ago
rom16384 14y ago
Hi. I'm trying use natural language generation (NLG) software, and found lots of long dead projects, two large lisp-based packages (FUF/SURGE, KMPL) that are not updated in years and not user friendly at all and a simple java package (SimpleNLG) that is indeed simple but not very sophisticated. Is this representative of the NLP/NLG software?
- PeterisP 14y ago
  Controlled languages are interesting for natural language generation purposes - for example, GF (http://www.grammaticalframework.org/ http://www.grammaticalframework.org/) may be useful for building sentences (in multiple languages, if needed) from an abstract data structure.
  - rom16384 14y ago
    GF seems very interesting, thank you.
pseut 14y ago
Really interesting article, especially since I'm an assistant prof idly considering the same sort of move. How much of a "business model" did you have before commitment -- did you have enough connections that you were confident you'd get funding once you had the idea mapped out in detail? Was UMass still a viable safety net, or were you fully committed?
HalcyonicStorm 14y ago
Random, but I love that the name is a play on the amazing movie "A Funny Thing Happened On the Way to the Forum" +1
- Evbn 14y ago
  It is a play on the name of the play.
javajosh 14y ago
Hi Aria. I have a question regarding the use of automatic sentiment analysis and it's relationship to choice. It seems to me that there is a fundamental divergence between the program of "give me what I will enjoy" and "give me what I need". It seems that your startup is focused entirely on the former question, and there's no doubt that if you are successful you will indeed be consuming more attention, which is of course the primary commodity in the attention economy. But wouldn't it be better to use NLP to emancipate people from the attention economy altogether, to help identify not what people want, but what they need to he happier, and more engaged in the real world doing real things for real people?
- dxbydt 14y ago
  >But wouldn't it be better to use NLP to emancipate people from the attention economy altogether I work on ads recommendations, and yes, it would be "better" if I stop recommending KFC to the 36% of obese Americans & instead recommend Crossfit or Yoga or Gold Gym or Myoplex. If I do that, they will quit the site en-masse and the negative engagement rates will go through the roof, I'll be out of a job, will end up eating at McDonalds to save money, and then become obese, and then click on the same KFC coupon recommended by another data scientist hired to replace me :) Yes, it would be "better" if people read the Economist instead of Cosmo, or went to grad school instead of building crud web apps, or watched Frontline PBS instead of Jerry Springer, but then, it would also be much "better" for the environment if we got rid of the 1000s of walmarts & safeways selling groceries & Uncle Sam shipped you healthy lettuce and spinach weekly via USPS....communism 101 :)
  - javajosh 14y ago
    Sorry you got downvoted - wasn't me, I swear (it actually annoys me that people use downvoting to mean "I disagree".) The problem with your comment is that you present a false choice. I believe that there is strong - very strong - demand for real, lasting happiness. Indeed I think that is the strongest demand there is. NLP and technologies like it can be at the core of the tools that help people choose who they want to be and help (not coerce) them to act consistency with those choices.
eternalban 14y ago
- Do you think you would have the opportunity to avail yourself of the fruits of "academia" if the current approach was fundamentally broken? - What would happen if viability of academic research was tied to one being a successful business person? (Asking in light of your comment elsewhere in this page re. "tenure system".)
nobody-special 14y ago
what are you dancing to? http://cdn.getprismatic.com/cdn/img/people/aria-bio__60cac850.gif http://cdn.getprismatic.com/cdn/img/people/aria-bio__60cac85...
carterschonwald 14y ago
Loved your post. Very articulate and nicely written. I've been amidst the academia -> industrial fun transition myself this past year, absolutely best decision i've made in the past half decade. One point you only lightly touched on, but which I think is worth restating is this: in academia theres this frustrating sense of "if you're not narrow, you can't be deep", whereas I see a lot of the more sophisticated bits of industry really valuing folks who strive for broad depth. Would you agree with that assessment? (admission: i'm presently having a go at building some tech products/tools that tie into a whole range of my researchy interests)

iamtheneal 14y ago

Awesome post. I -- along with many of my colleagues from grad school -- have had pretty similar experiences with academia (minus the outlook for a promising academic career ;) ). This sort of thing (very smart people abandoning academia) is going to continue to happen unless academia figures out a way to make itself more relevant. academic |ˌakəˈdemik| adjective 2 not of practical relevance; of only theoretical interest : the debate has been largely academic.

hyperbovine 14y ago
My experience in academia thus far: for every five smart people abandoning academia for industry, one truly brilliant person remains behind. That's all that is required for the model to sustain. (And even then, there are not enough academic jobs to go around.)

junktest 14y ago

Zite too seems to be working in the same space of ML-aided personalized news magazines.

mikeklaas 14y ago
Several of us Zite employees are also refugees from academia, it turns out.

jamesjporter 14y ago

Great post. As someone who works in a different field of science, one bit got me thinking: >Like any academic community, the work within NLP had become largely an internal dialogue about approaches to problems the community had itself reified into importance. I would argue that this is an issue of goals. If you're motivated by the application of research results to solve practical problems (as the author is), then this is a valid criticism. But for me science is also self evidently valuable — understanding the principles that govern the universe is a noble goal irrespective of finding opportunities to apply them. Perhaps the field plays a role as well. In all sciences one's goal is to discover the rules and facts that govern a particular system. In the natural sciences, this system happens to be the world in which we live, whereas in the formal sciences (math / CS), the system is often an artificial one of human construction. In the natural sciences, the importance of the rules you discover is self evident (they govern our own lives and capabilities!), whereas in the formal sciences, its more necessary to justify the importance of your discoveries (with, say, practical applications) because the importance of the system you're studying isn't as self-evident. This isn't to say that the natural sciences are in some way superior; just a speculation about the attitudes/motivations of academics in different fields.

iyulaev 14y ago
In the natural sciences, this system happens to be the world in which we live Not to say I disagree with your post, but it's it more accurate to say that the natural sciences today explore models for the world in which we live? The models tend to be fairly obvious for things on the human scale, but when you talk about systems on the atomic scale, or on the cosmic scale, the immediacy of the models tends to break down. The result is that, just as for the abstract sciences (math, CS, etc), the usefulness of the models has to be justified. So, I feel that the line between purely abstract sciences and "natural sciences" is not quite as fine and well-defined as your post makes it to be.
- tsewlliw 14y ago
  I really like knowing that there are people dedicated to thinking deep thoughts. There was a recent potential proof published on a tough math problem, and apparently the author had gone dark for 15 years creating a fantastic mathematical universe and vocabulary all on his own. Thats worthwhile. Maybe not for everyone to go off doing it, but definitely for some.

betula82 14y ago

Do you have ideas for how academia can be brought back into touch, or is it a lost cause?

aria 14y ago
Well, I think the number one thing that would correct the balance between academia and industry is if people could freely go from one to the other. Someone could take insights from one arena to the other, enriching both. There are many reasons why this is difficult, but the primary obstacle is the tenure system.
- opminion 14y ago
  In the UK it is possible to switch between academia and industry, so long as you are satisfied with fixed term contracts in academia. Recruiters tend to get confused when someone turns at their doorstep with a PhD ("which marks did you get?"), and academics tend to not have a clue of what's the benefit of industrial experience (in spite of being effectively "agile" product managers themselves when participating in, say, a European Framework project).

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sbashyal 14y ago

Having spent several years doing academic research before finally leaving to work on real-world problems in machine learning and NLP, I can relate to this article. If any of you have problems in this domain, I am interested to chat.

marshray 14y ago

A really fantastic article overall. I was never personally at risk of academia, so I don't resonate with that part of the article. But I particularly liked these two sentences for their practical insight: that process of taking qualitative ideas and struggling to represent them computationally is the core of artificial intelligence (AI). and that path from research to product rarely works, and when it does it's because a company is built with research at its core

aria 14y ago
Thanks! It seems like an obvious thing, but thinking about "operationalizing" intuitions computationally really helped me hone in on what I should be focusing on with research. My advisor Dan Klein was really awesome at teaching that.

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HalcyonicStorm 14y ago

I love that the name is a play on the amazing movie "A Funny Thing Happened On the Way to the Forum" +1

galois198 14y ago

I was wondering, is it possible for individuals with no formal ML background to implement algorithms with as much subtlety as Prismatic?

aria 14y ago
Building Prismatic is way more than just about having a formal ML background. It's that along with large-scale systems skills and having a sixth sense for working with data (text especially) and knowing what simple ideas will work and what needs to be complicated. So to answer your question yes, you need a formal ML background but you need a lot else. Luckily, you can pick up all these skills from online courses, real world building, and a lot of self study and improvement

jacoblyles 14y ago

There are a lot of good ideas and sentiments in this article. And then at the end I find out the trail-blazing product he left academia for is "a newsfeed based on your interests." How many startups like this are there now? 300? That is probably a low estimate. I'm sure that everyone living in the Valley personally knows at least one founder working on the exact same product. And none of them are better than my Hacker News/ Facebook/ Reddit/ RSS feed combo. I've heard some of the many Prismatic competitors describe themselves as "a Pandora for news" which is an apt description, since rdio, soundcloud, and Spotify are better than Pandora. Self, social and community sourcing for digital entertainment tends to be better than algorithms. While I believe the "problem" domain is severely overworked, if you're going to stick with it then my bet is that social algorithms like collaborative filtering a la Netflix does a better job than topic modeling. On the optimistic side, a good company is more than a single product. Maybe the author's considerable expertise and experience from building Prismatic will lead to something cool down the road.

xaa 14y ago
My feelings exactly. It's made worse by the fact that, out of all the academic departments out there, AI and NLP research has perhaps the greatest potential to transform society in so many ways. He leaves the field trying to create intelligent machines in order to write a Google News clone? I truly don't get it.
- IheartApplesDix 14y ago
  Then I don't think I can explain it to you. If you use HN and don't understand the impact of this work.. well there's a forest I'd like to show you. Amazon self publishing is just another publishing outlet. Google is just another index page. HN is just another alt.computer board.
  - stephengillie 14y ago
    To me, it feels like this person's talent is wasted on this project. With such a strong background in natural language processing, why isn't this person involved in a Siri competitor, in Web real time chat, VOIP compression, or AI speech? Is this the limited scope at which a typical CS Ph.D operates? Reach for the stars. Let people of lesser ability make news apps, even if it's a struggle for them.

yawgmoth 14y ago

I signed up to see how accurate it could be - the interests outlined in the e-mail I received seem pretty accurate but the stories that are being displayed have nothing to do with those topics. There was a dearth of interesting reading material.

zissou 14y ago

I faced a similar problem in academia, but it was in economics. I started my undergrad career as a computer science major, later ending up in economics, and I went on for my PhD in economics after finishing my BA. For those that aren't familiar, a PhD in economics is a lot like a PhD in mathematics. If you don't already respect economists mathematical ability, you really should, but that's not my point here because math is just a tool, and contains no absolute truths for the social scientist. In an effort to combine solid theoretical research with well built empirical models, I learned how to program Python to scrape data from web sites. Since nobody around me knew anything about computer science, I found myself having to teach myself everything when it came to "how would I write a program that collects X things from Y products in Z Internet markets". In the beginning, when I was learning to use Python libraries for doing HTTP requests (eventually converging to using 'requests'), how to parse that HTML (started with BeautifulSoup and then converged to 'lxml'), and how to aggregate and analyze that data (eventually converging to 'pandas'), I had to spend a lot of time learning the ins and outs of Python. To this day, I still think it was a great choice because Python has changed the way I approach any kind of business question that could be answered with a well defined empirical model. As a research assistant, I would spend 12 hours writing scripts to automate the collection and analysis of data for some project I discussed with a professor. The day after writing that script, I would go and talk to the professor and want to discuss some of the computational issues with the script (say, encoding issues, or even the use of computers on EC2 to help collect massive amounts of data every day), but the economics professors would not care at all to hear about any of that. "You need to be studying the economics, not the computer science" they'd tell me. This would infuriate me, because in my mind, if you wanted to be able to ask all these interesting questions that rely on the data, then you need to spend time to make sure you've done the computation correctly and in a way that is reliable. Maybe I dug my own grave by showing my excitement as I began to become more fluent with Python, and thus more confident in my abilities. Nonetheless, I eventually decided to leave my PhD program because my interests in topics that lie at the intersection of computer science and economics were a bad fit for my program. It was so disheartening to me because I truly loved economics, and was confident that what I intended to do with my PhD research was going to be unique and lay a framework for the field of industrial organization. However, the experience I received in my program was the lack of an adviser that could truly help me achieve what I wanted to do, and a regular negative response to anything I'd bring up that was out of the realm of what my professors were used to talking to graduate students about. Overall, as my tone may signal, graduate school has left me very, very bitter.

hna0002 14y ago

http://techcrunch.com/2012/12/05/prismatic/ http://techcrunch.com/2012/12/05/prismatic/

mitultiwari 14y ago

Nicely written blog! Agree with the author that academia sometimes focusses on a very narrow band of research topics, which might or might not improve end user experience. Also, agree with the author that personalized news has very interesting NLP+Machine Learning problems. However, I am not convinced that personalized news is what users wants, and whether users want to discover popular news and articles by serendipity, socially, rather than personalization by algorithms. Further, I think personalized news has very limited opportunity for generating significant revenue.

jacoblyles 14y ago
My suspicion about personalized news is that entrepreneurs are building things they know how to build rather than building something people want.

Irishsteve 14y ago

What exactly do people get out of all these news aggregators? I'd imagine the front page of reddit or at least alocalised version is more interesting than a personilised version. When does it go from news to infotainment? And if thats not the case why would someone think something beyond simple facebook like or twitter comment extractions is a big deal? I've seen lots of papers where representing a web page and a user in a vector space based on TFIDF performs well. I've even see Yahoo research post slides about using some form of random bucket for news recommendation because the novelty of newer / stranger articles improves ad click throughs. Then again did this article come out the same time as the PR release about funding for their company? If thats the case is this just a wide scale PR initiative?