12 ms·

Deep-Fried Data

560 points by udba 10y ago

sdenton4 10y ago
"...Dim witted grad student that you can't really trust..." Reminds me of the phrase "graduate student descent" for training neural networks... I've been noticing more casual dismissiveness towards grad students lately. They are certainly often treated as the grunt laborers of academia, in areas where career prospects are downright stupid. I generally feel it would be more productive to at least pretend that they're being trained to be independent, aggressive researchers in their own right, though.
- deleted 10y ago
  [deleted]
- gabrielgoh 10y ago
  grad students are put in the same category as interns and teenagers, a naive type of person still in the making. i dont think there's any ill will intended.
  - eanzenberg 10y ago
    You are dim witted. No ill will intended.
    - edmccard 10y ago
      >No ill will intended. Is that a new short version of Hanlon's Razor?
    - elmigranto 10y ago
      There's a difference between metaphors/jokes and insults addressed at you personally.
- nullc 10y ago
  Considering the working conditions and prospects for the future that graduate students face, one /could/ argue that that a selection bias should be expected there. > to at least pretend that they're being trained to be independent, aggressive researchers But that is the issue, isn't it-- it would be pretending.
- vilhelm_s 10y ago
  Yeah, I also thought this metaphor seemed weird. "Now you need some adult supervision in the room", but grad students are, in fact, adults. And not particularly dim-witted, as a rule.
- munin 10y ago
  looks like we found the grad student! but seriously, as a grad student, absolutely no one gives us respect. not our peers, our bosses, or society. why would you expect some random on the internet to do better?
  - deleted 10y ago
    [deleted]
1024core 10y ago
"The names keep changing—it used to be unsupervised learning, now it’s called big data or deep learning or AI" Um, I'm sorry, but unsupervised learning and deep learning are not the same.
- idlewords 10y ago
  What's the distinction?
  - absherwin 10y ago
    Unsupervised refers to whether or not the dataset is being trained against anything. Think about the difference between: How many people will view this webpage? Divide these pages into 20 clusters? The first is supervised. The second isn't. Deep learning refers to a particular type of a particular learning technique: Specifically a neural network that has many hidden (intermediate) layers. Deep learning can be used for either supervised or unsupervised learning.
    - idlewords 10y ago
      Thanks for the explanation! I was remembering what flavors of snake oil were being peddled to people in the humanities in the early 2000's, and didn't mean to muddy the waters around technical terms of art.
    - gabrielgoh 10y ago
      I agree with your sentiment, it feels out of place because deep learning, AI and big data are buzzwords, but unsupervised learning is a rather technical term in machine learning referring to a very specific class of problems.
      - apathy 10y ago
        Specific only in that the categories aren't supervised. Furthermore, suppose you have labels for some but not all points on your data (i.e. your model is designed to be robust in the face of things it hasn't been trained for). There are a nontrivial number of people who work on either side of the "semi-supervised" divide, e.g. clustering with examplars or pulling out the generative model for a discriminative task. Personally I like these better, as they're more akin to what people seem to actually do (encounter new things and try to make sense of them). Anyways. If you look at the delta in performance between "old" techniques like random forests or gradient boosting vs. deep convolutional networks, it tends to be quite small until your datasets grow to very large sizes. For things like images that's not much of a problem. For things like rare diseases it's a huge problem.
marklyon 10y ago
I provide guidance to attorneys involved in the discovery process; "Technology Assisted Review" is of huge interest to those teams, as it allows them to leverage coding on a small sample of the population across a much larger set of documents. For many cases, the cost and (occasional) time savings is instantly attractive. Sadly, the process is hard to do well. Far too many screw it up in new and amazing ways. The author's concerns over machine learning are well-founded. The best option I've been able to identify to ameliorate some of the concerns is focusing on the population that will be suppressed. Once the model returns the desired recall / precision, drawing samples from the excluded population with a rigorous acceptance standard can help validate whether you've simply built a model around your biases. Couple that with allowing an opponent to validate a randomly-selected sample and you've cleared up a lot of the uncertainty in the model. It's not perfection, but perfection is a very difficult standard.
- abofh 10y ago
  The issue with that approach is ensuring the suppressed are represented. When it's black vs white, you can oversample one and be done. However, if there's any winner take all built into the system, there's a strong incentive to not even acknowledging dissent.
curuinor 10y ago
Rather hilariously, deep frying is already a term of art in ML, of course in a radically different setting. Deep fried convnets (https://arxiv.org/abs/1412.7149 https://arxiv.org/abs/1412.7149).
- argonaut 10y ago
  One (not especially widely read) paper's title can hardly be called a "term of art" in ML.
skybrian 10y ago
If you think the Internet is as safe and controlled as a shopping mall, you probably should be reading Krebs on Security more. People tend to move towards the more mall-like areas of the Internet due to spam and abuse that they don't want to deal with. This can be low-level stuff, or (as in the cases of Kreb himeself) sometimes the attackers get out the big guns, and you need to run for cover. And that's why we're hanging out here, after all, and not in some unmoderated forum. And even here, post on certain subjects and conversation quickly degenerates. I think we do need a wider variety of spaces to hang out, though. No set of rules works for everyone. And if you do want 4chan, you know where to find it.
- aab0 10y ago
  > If you think the Internet is as safe and controlled as a shopping mall, you probably should be reading Krebs on Security more. That's an amusing comparison, given how much of Krebs focuses on offline ATM skimming, copying credit cards at point-of-sale terminals, hacking major retailers's CC databases, and using stolen cards at retail and mall stores to cash them out...
udba 10y ago
I'm currently applying for co-op jobs (internships) and while trawling the university job board I've seen many positions requiring big data this or machine learning that. What's not clear to me is why companies who don't seem to have any need for machine learning team (i.e. a subscription box company) are looking to hire one. Surely part of this can be pinned down to the hype associated with ML that may well die out, but the proliferation of these tools doesn't bode well for Maciej's dream of a weird, creative, and interesting internet.
- teej 10y ago
  These companies aren't looking for someone to develop new machine learning techniques, they are just looking for someone who can slap together existing utilities to meet their goals. Companies that run on subscription literally live and die by their churn rate. It is both feasible and reasonable for a subscription box company to hire someone to use machine learning to build a predictive churn model. That may seem trivial to you but that's the reality behind those job posts.
chewxy 10y ago
Regarding Maciej's fears about machine learning - I've written about this before, and even right now I'm not sure where I stand exactly, except that tweaking the algorithms to compensate for bias is definitely not the right answer: if you look at the mirror and don't like what you see, you don't draw on top of the mirror to accentuate the result! You go on a diet! I liked the idea of data gardening, but the thought of going-to-communities is daunting. I get tired even thinking about it. Regarding living beyond walled gardens: > Publish your texts as text. Let the images be images. Put them behind URLs and then commit to keeping them there. A URL should be a promise. But people already do that! The question now is to turn to why people do otherwise. I personally do not understand the reason people say, post long blogposts on Facebook, but I do understand for services like Medium. For example, I'm extremely tempted to write on Medium because it provides the network effects of readers clicking on tags to read next. So the question is how do we democratize that?
- big_surprise 10y ago
  So the question is how do we democratize that? Commenter wtracy has already linked to the FSF's list of High Priority Free Software Projects... From there, look into what they have to say about free wifi (and in particular, but not limited to the OrangeMesh package): http://www.fsf.org/campaigns/priority-projects/free-software-drivers-for-network-routers http://www.fsf.org/campaigns/priority-projects/free-software... If a convincing case could be made that the benefits to National Security outweigh the costs to the copyright cartels, I'd be willing to bet that young secondary-schoolers would have a blast with a decently designed curriculum that includes a working student-to-student mesh-network as one of its goals.
  - chewxy 10y ago
    I actually meant democratizing the network effect that Medium has. The "free marketing" bit. I mean, right now one can pretty freely go write up a blog using self-hosted wordpress, octopress, pelican, hugo or whatever. But choosing that over Medium can sometimes mean a lot more work to put in. But if we can democratize the ease-of-use and the good bits of Medium/Facebook/Twitter... Maciej's end statement about "using open standards, write text in text, images in images" would have been achieved. The problem is that corporations now create a significantly more compelling version (in most criteria - UX, UI, etc) of the Free and Open versions out there.
makomk 10y ago
Have to admit that I didn't expect to see that quirk of LiveJournal culture mentioned in an article on the HN front page, let alone in a speech to the Library of Congress. It just sort of faded away without really influencing the current generation of social networks. Also, it's funny how the net changes, how unthinkable it is to have a social network that doesn't slice up people's data and use it to advertise to them now compared to how anti-advertising LiveJournal was back then. Not convinced it's a change for the better.
- idlewords 10y ago
  I'm the guy who gave this talk. To add to the funny, LiveJournal hired me to rewrite their ad engine in 2007. I did a horrible job at it, but turned my ineptitude into a principled and lucrative ideological stance that I have milked ever since. Don't be afraid to pivot.
  - embarcadero 10y ago
    Was this recorded? Link?
    - pauldino 10y ago
      There's a YouTube link at the top of the page. https://www.youtube.com/watch?v=8gcu2GQf7PI&feature=youtu.be&t=5h31m50s https://www.youtube.com/watch?v=8gcu2GQf7PI&feature=youtu.be...
  - bo1024 10y ago
    I enjoyed reading it a lot, thank you. I think about these issues a lot and you gave me new things to think about / crystallized some nice perspectives.
pimlottc 10y ago
> Many [programmers] work jobs that are intellectually stimulating, but ultimately leave nothing behind. There is a large population of technical people who would enjoy contributing to something lasting. This hits pretty close to home.
- leesalminen 10y ago
  Same here. I was just talking with a friend last night about how software developers should have a creed, like how doctors have the Hippocratic oath. We could potentially cause far more harm than doctors nowadays.
  - bthdonohue 10y ago
    As part of my computer science program in college, we studied the ACM's Software Engineering Code of Ethics and Professional Practice, which in effect is what you describe. http://www.acm.org/about/se-code http://www.acm.org/about/se-code
    - cmrx64 10y ago
      And as an aside, the ACM is currently collecting comments on revisions to their code of conduct. http://ethics.acm.org/code-of-ethics/code-2018/ http://ethics.acm.org/code-of-ethics/code-2018/
  - mamp 10y ago
    Interesting, but note that the Hippocratic Oath doesn't work so well with preventable errors in health care the 3rd leading cause of death in the US https://www.washingtonpost.com/news/to-your-health/wp/2016/05/03/researchers-medical-errors-now-third-leading-cause-of-death-in-united-states/ https://www.washingtonpost.com/news/to-your-health/wp/2016/0...
- keyle 10y ago
  Same here. I'm battling with this thought a lot. Beyond jobs, I think there should be communities of developers, designers, producers, writers, getting together and figuring out this stuff. And I don't mean open source projects. Let's group together smart people wanting to make a difference and have a hit list of things we (people) actually need. A group that would organise people into mission driven development. I'm so fed up of getting paid to potentially make founders rich. Or to be a small cog in a gigantic machine on a slow decline. I'm also unemployable because I can't buy into the corporate BS anymore. And where I am, there doesn't seem to be design/dev jobs that actually want to make a difference. It's an economy problem. The startup thing seems to be the best way we go about solving problems in the world today. But if you happen to _not_ be at the right place at the right time, meeting the right people, poof, it's gone. I can't imagine that an advanced specie would operate this way. We should be focused on solving problems, instead of being focused on escaping the rat race, to then be able to solve problems. I'm glad I am not alone seeking purpose. There goes a point where you're technically advanced, you have itches to fix things and all you see is the broken economy of consumerism and "let's give kids video clips and smileys, derp".
qwertyuiop924 10y ago
>the Internet is a shopping mall. There are two big anchor stores, Facebook and Google, at either end. There’s an Apple store in the middle, along with a Sharper Image where they are trying to sell us the Internet of Things. A couple of punk kids hang out in the food court, but they don't really make trouble. This mall is well-policed and has security cameras everywhere. And you guys are the bookmobile in the parking lot, put there to try to make it classy. It's already been mentioned, but this guy needs to get out a bit more. The internet is a city. There's the specialist shops (HN), the bustling malls (Reddit, YT), the shady back alleys (4chan, 8chan etc.), the historical districts (Usenet, Archive.org), the cafes (IRC, ICQ, Slack, etc.). To their credit, the author is more knowledgeable than most, however. I see so many dismiss the internet as just Facebook, or YouTube, discuss trolling as if it's a single phenomenon, and it's a recent thing, associated with Social Media. So many think that there's an internet culture: there isn't: there's a set of almost infinite numbers of overlapping, interlinked cultures. I can even map out the origins and historical influences of a few. There are even a few who think that social media sites are good forums of discussion. The poor sods: the Usenet was a better discussion forum than Facebook ever was, and the Usenet's not that great. If you really want to see what the internet is like (that isn't advice for the author: I'm pretty sure the mall analogy doesn't encompass his internet experience, and is merely an analogue I find odd), explore. See it all, in all of its weird, wacky, zany, jokey, serious, offensive, manic, smart, stupid, brilliant, insane glory. I promise you, you won't be dissapointed. People ask me why I'm not on social media. It's because social media is boring. Unlike Reddit, 4chan, and the rest, not much interesting happens. Unlike HN, I'm not likely to be intellectually stimulated, or learn something new. Unlike static sites, I don't get to see that kind of wild creativeness that personal webspace tends to invite in hackers, nerds, and others who know what makes the web tick. I don't want to see what you ate, I don't want to see your cat, I don't want to hear banal details about your everyday life. I want to hear something intersting, new, and original. I want to hear the next Ze Frank, or Tom Ridgewell, or Simon Travaglia, or Steve Yegge, or RMS, or PG, or Ryan Dahl, and you can bet I won't on a site with a signal:noise ratio that high. People also ask why I'm fascinated with the internet. My response is, why wouldn't I be? It's a catalogue of decades of human creativity and interaction. It's open mike night at the largest club in the world, which is also a discussion forum, and a shady back alley, and a convention. It is - to borrow and butcher Sir Terry's words - like being blindfolded and drunk at several different parties at once. But, in what it rapidly becoming the sign-off on my incoherent, long-winded ramblings that are really only tangentially connected to the topic at hand, maybe I'm just totally mad. EDIT: tried to clarify that I wasn't trying to insult the author. Not my intent, but it seemed to come off that way. It still does, but less so, and I prefer not to edit my old content too much. Also, I just checked out pinboard. Pinboard is amazing, and I am impressed. Basically, don't take this as anything more than a tangential, incoherent ramble started by an analogy the author used which I found unrepresentative. Because that's what it is.
Esau 10y ago
"And this time it's not the government, but the commercial Internet that has worked so hard to dismantle privacy." So true.
leesalminen 10y ago
> For the generation growing up now, the Internet is their window on the world. They take it for granted. It’s only us, who have seen it take shape, and are aware of all the ways it could have been different, who understand that it's fragile, contingent. The coming years will decide to what extent the Internet be a medium for consumption, to what extent it will lift people up, and to what extent it will become a tool of social control. I agree completely. This is something we should be cognizant of.
morecoffee 10y ago
Giving up control is harder than the author makes it seem. It isn't so much that you give it up, but that you give _to_ someone else. Picking that someone else is extremely difficult and a wrong choice will destroy your community. Using machine learning on the other hand is a safe bet. It is much easier, I would assert, to write machine learning code to organize data than to curate a community of humans to organize data. The ML approach will do pretty good even if it isn't the best, which is why it's what everyone is switching to. Keeping with the author's example, is it easier to organize erotic fanfic with a computer, or enable a community to do it without spiraling out of control?
- crzwdjk 10y ago
  For example, it is clearly easier to write a machine learning system to find interesting articles and highlight insightful commentary, compared to using something so crude as a group of people on a website collectively voting on which stories and comments they like... wait a minute...
erichocean 10y ago
> Publish your texts as text. Let the images be images. Put them behind URLs and then commit to keeping them there. I sounds like he's saying ephemeral content is worthless and should be shunned. I, and hundreds of millions of others, disagree. You want a bland, awful, boring society? Easy: make everything you do stick around forever—like a promise. And then watch the world self-police as the lifeblood drains out of it. You'll get…Facebook. No thanks.
- idlewords 10y ago
  The audience for this talk was people with very large collections they're bringing online. I was trying to encourage them to avoid exotic formats, custom plugins, custom software (shudder) when they put this material online, and make them web accessible. For example, here is three quarters of a PETABYTE of historical American newspapers: http://chroniclingamerica.loc.gov http://chroniclingamerica.loc.gov
  - erichocean 10y ago
    Okay, that makes sense. I 100% agree that bringing collections online in exotic formats is a terrible idea.
Asparagirl 10y ago
> I’ve saluted the efforts of Archive Team and the Internet Archive, but their activity is like having a museum curator that rides around in a fire truck, looking for burning buildings to pull antiques from. It's heroic, it's admirable, but it’s no way to run a culture. ...but in the meantime, here's an obligatory and shameless plug for donating to the Internet Archive[1] (tax-deductible in the US), or better yet making a recurring monthly donation so they can more accurately forecast revenue for the year, or better still getting your employer to make a nice big donation to this crucial bit of Internet memorybanks. And as for Archive Team, we're always looking for a few good geeks.[2] Run an instance of the Warrior on spare cloud servers, or help patch and ship code at GitHub.[3] [1] http://archive.org/donate/ http://archive.org/donate/ [2] http://archiveteam.org/index.php?title=Main_Page http://archiveteam.org/index.php?title=Main_Page [3] https://github.com/ArchiveTeam/ArchiveBot https://github.com/ArchiveTeam/ArchiveBot
- codezero 10y ago
  I've got a VPS sitting around doing very little – what's the easiest way to get started?
  - Asparagirl 10y ago
    Run a Warrior! Many flavors available: VirtualBox, Dockerfile, AMI (for Amazon EC2), you name it. http://archiveteam.org/index.php?title=ArchiveTeam_Warrior http://archiveteam.org/index.php?title=ArchiveTeam_Warrior It would deeply unethical for me to point out that you could also run the Warrior on free server space that your company might not notice, kind of like the karmic inverse of a bitcoin miner. Deeply unethical. So I won't mention it.
    - deleted 10y ago
      [deleted]
- dcposch 10y ago
  The Archive is awesome, but the author's sensationalist description of what they do isn't really accurate. For the most part, archive.org is not rushing in to save stuff that's about to be deleted. Instead they are crawling the web 24/7, patiently maintaining a historical record. Check out http://oldweb.today http://oldweb.today It is amazing
aub3bhat 10y ago
Frankly as a grad student (The kind that the author apparently considers "dim witted"), the entire article is meaningless babbling without any underlying theme. I wonder if the author truly understands "Machine Learning", what are his qualifications? A degree in Art History, and some "programming experience" aren't very assuring. E.g. >> "The names keep changing—it used to be unsupervised learning, now it’s called big data or deep learning or AI" WTF?? The author should enroll in a beginner Machine Learning course on Udacity or Coursera before making philosophical statements about fields he has zero clue about. It seems the only skill the author has is piecing together meaningless arguments that appeals to average HN users incapable of distinguishing between informed opinions and pseudo-scientific rants. Hell at least bad graduate students have to give examinations, read papers and make original contributions that get peer reviewed (otherwise they fail/get-kicked-out/drop-out). Not like this guy who does not understands difference between "supervised" and "unsupervised" machine learning, yet feels comfortable in making "prophetic" statements about machine learning. Also >>> "These techniques are effective, but the fact that the same generic approach works across a wide range of domains should make you suspicious about how much insight it's adding." What does he means by "same generic approach". If we assume he is implying specific algorithms then we have a good "No free lunch" theorem that shows that a single algorithm is not effective across all domains. Now if by "generic approach" the author mean "machine learning" in general then its as ridiculous as saying "Mathematics is effective, but the fact that the same Mathematical approach works across a wide range of domains should make you suspicious about how much insight it's adding." The entire article is filled with "truthiness" and "feel-good" statements, which fall apart on closer examination.
- idlewords 10y ago
  My degree was in studio art, not art history.
  - aub3bhat 10y ago
    Those two are still orders of magnitude closer to each other when compared to difference between unsupervised learning with deep learning.
pcmaffey 10y ago
Machine learning does not have less bias than human researchers. It is simply magnified at scale. And that scale is exactly the state of the internet. There is so much data available to study and understand, that we absolutely need better tools, like machine learning or whatever we want to call it, to help us keep up. Shit's moving faster than our human perception can handle, especially for those who didn't grow up with the internet. Yes the data analyctic tools we have right now are premature— like fast food to our productized minds— but they will improve rapidly, as our taste for quality improves. But sure demonizing the things you don't like is one step on the path to learning what's truly valuable.
- coldtea 10y ago
  >Machine learning does not have less bias than human researchers. It is simply magnified at scale. Scale differences can and often do lead to qualitative differences. Individual (or aggregate) human researchers are not hooked up in huge services to make inferences and deductions automatically about billions of people. Besides those machine learning tools, beside the huge data sets, are programmed in their general framework by human researchers, and are given weights, constraints, and fine-tuning by them, so they have both kinds of biases. >But sure demonizing the things you don't like is one step on the path to learning what's truly valuable. So, kind of like disparaging via a straw-man a speech that offers detailed argumentation?
  - AndrewKemendo 10y ago
    Individual (or aggregate) human researchers are not hooked up in huge services to make inferences and deductions automatically about billions of people Yes they (we) are. It's the same data set. TV, movies, papers, internet videos et al. is all the same biased, labeled data that is being fed (watched, listened to etc...) to machines. You automatically make inferences and deduce things about people based on labeling and training of your brain. You're constantly fine tuning by getting new weights about things through interactions with others and media.
    - coldtea 10y ago
jaywunder 10y ago
I don't think I understand what the exact point of this talk was. Maybe the thesis was stated at the end of the talk when he said that he wishes the internet were more like a city rather than a mall. I think the internet can be like a city, and I think a great example of a place where people with conflicting ideas talk together is HN. Sure HN can be an echo chamber at times. But there's quite a few times when people with differing opinions talk about their different opinions. Also I don't necessarily understand Ceglowski's stance on why we shouldn't use deep learning and should avoid surveillance on the web. I don't take issue with becoming a datapoint in Facebook's web of people because nothing bad has happened or can happen from me giving Facebook my data. When most people speak out about the data that's being collected about Facebook and Google users they say they're "worried about what could happen" but then never list any bad things that they're actually afraid of. The speaker falls to this issue too. Ceglowski says: >I worry about legitimizing a culture of universal surveillance. But then never explains what bad could happen from legitimizing that culture. Maybe I'm completely missing the point of the talk? Please explain what I'm missing if I'm actually missing something.
- idlewords 10y ago
  The audience for this talk was a bunch of librarians and fellow travelers who are bringing large archives and collections online, often at great expense. I wanted to encourage them to find new, engaged audiences for these collections, rather than fixate on how to analyze them with computers. With regard to the dangers of surveillance, I've made a sustained argument about this in other talks. It boils down to the data being collected having great power to harm people if it is ever put to malicious use, and a lifespan that exceeds that of institutions we know how to run. My beef is not with the surveillance alone, but with the combination of surveillance and permanent storage.
  - jaywunder 10y ago
    Thank you for explaining that! The context is meaningful and makes your talk make sense. On the regard of data talking into the wrong hands, I take issue to this argument because it's not a unique problem to personal data collection. Any data could be hacked - bank information, address, whatever. But that doesn't mean we don't use the internet for banking and etc. It means we try to make systems that are difficult to hack. It seems like you'd want data collection not to happen on websites like Facebook and Google, when hacking isn't a unique problem to those websites.
goldmar 10y ago
Thank you for this article. I have really enjoyed your writing style, especially the creative metaphors you're been using :)
dvdplm 10y ago
Idelwords is one of those blogs worth dropping everything you do and just take a deep breath and dive in and revel in the joy of clear thought expressed through clear prose. Love it. Thanks.
TranceMan 10y ago
I have been having similar thoughts for a while: https://news.ycombinator.com/item?id=10937201 https://news.ycombinator.com/item?id=10937201

560 points by udba 10y ago

"...Dim witted grad student that you can't really trust..." Reminds me of the phrase "graduate student descent" for training neural networks... I've been noticing more casual dismissiveness towards grad students lately. They are certainly often treated as the grunt laborers of academia, in areas where career prospects are downright stupid. I generally feel it would be more productive to at least pretend that they're being trained to be independent, aggressive researchers in their own right, though.

deleted 10y ago
[deleted]
gabrielgoh 10y ago
grad students are put in the same category as interns and teenagers, a naive type of person still in the making. i dont think there's any ill will intended.
- eanzenberg 10y ago
  You are dim witted. No ill will intended.
  - edmccard 10y ago
    >No ill will intended. Is that a new short version of Hanlon's Razor?
  - elmigranto 10y ago
    There's a difference between metaphors/jokes and insults addressed at you personally.
nullc 10y ago
Considering the working conditions and prospects for the future that graduate students face, one /could/ argue that that a selection bias should be expected there. > to at least pretend that they're being trained to be independent, aggressive researchers But that is the issue, isn't it-- it would be pretending.
vilhelm_s 10y ago
Yeah, I also thought this metaphor seemed weird. "Now you need some adult supervision in the room", but grad students are, in fact, adults. And not particularly dim-witted, as a rule.
munin 10y ago
looks like we found the grad student! but seriously, as a grad student, absolutely no one gives us respect. not our peers, our bosses, or society. why would you expect some random on the internet to do better?
- deleted 10y ago
  [deleted]

1024core 10y ago

"The names keep changing—it used to be unsupervised learning, now it’s called big data or deep learning or AI" Um, I'm sorry, but unsupervised learning and deep learning are not the same.

idlewords 10y ago
What's the distinction?
- absherwin 10y ago
  Unsupervised refers to whether or not the dataset is being trained against anything. Think about the difference between: How many people will view this webpage? Divide these pages into 20 clusters? The first is supervised. The second isn't. Deep learning refers to a particular type of a particular learning technique: Specifically a neural network that has many hidden (intermediate) layers. Deep learning can be used for either supervised or unsupervised learning.
  - idlewords 10y ago
    Thanks for the explanation! I was remembering what flavors of snake oil were being peddled to people in the humanities in the early 2000's, and didn't mean to muddy the waters around technical terms of art.
  - gabrielgoh 10y ago
    I agree with your sentiment, it feels out of place because deep learning, AI and big data are buzzwords, but unsupervised learning is a rather technical term in machine learning referring to a very specific class of problems.
    - apathy 10y ago
      Specific only in that the categories aren't supervised. Furthermore, suppose you have labels for some but not all points on your data (i.e. your model is designed to be robust in the face of things it hasn't been trained for). There are a nontrivial number of people who work on either side of the "semi-supervised" divide, e.g. clustering with examplars or pulling out the generative model for a discriminative task. Personally I like these better, as they're more akin to what people seem to actually do (encounter new things and try to make sense of them). Anyways. If you look at the delta in performance between "old" techniques like random forests or gradient boosting vs. deep convolutional networks, it tends to be quite small until your datasets grow to very large sizes. For things like images that's not much of a problem. For things like rare diseases it's a huge problem.

marklyon 10y ago

I provide guidance to attorneys involved in the discovery process; "Technology Assisted Review" is of huge interest to those teams, as it allows them to leverage coding on a small sample of the population across a much larger set of documents. For many cases, the cost and (occasional) time savings is instantly attractive. Sadly, the process is hard to do well. Far too many screw it up in new and amazing ways. The author's concerns over machine learning are well-founded. The best option I've been able to identify to ameliorate some of the concerns is focusing on the population that will be suppressed. Once the model returns the desired recall / precision, drawing samples from the excluded population with a rigorous acceptance standard can help validate whether you've simply built a model around your biases. Couple that with allowing an opponent to validate a randomly-selected sample and you've cleared up a lot of the uncertainty in the model. It's not perfection, but perfection is a very difficult standard.

abofh 10y ago
The issue with that approach is ensuring the suppressed are represented. When it's black vs white, you can oversample one and be done. However, if there's any winner take all built into the system, there's a strong incentive to not even acknowledging dissent.

curuinor 10y ago

Rather hilariously, deep frying is already a term of art in ML, of course in a radically different setting. Deep fried convnets (https://arxiv.org/abs/1412.7149 https://arxiv.org/abs/1412.7149).

argonaut 10y ago
One (not especially widely read) paper's title can hardly be called a "term of art" in ML.

skybrian 10y ago

If you think the Internet is as safe and controlled as a shopping mall, you probably should be reading Krebs on Security more. People tend to move towards the more mall-like areas of the Internet due to spam and abuse that they don't want to deal with. This can be low-level stuff, or (as in the cases of Kreb himeself) sometimes the attackers get out the big guns, and you need to run for cover. And that's why we're hanging out here, after all, and not in some unmoderated forum. And even here, post on certain subjects and conversation quickly degenerates. I think we do need a wider variety of spaces to hang out, though. No set of rules works for everyone. And if you do want 4chan, you know where to find it.

aab0 10y ago
> If you think the Internet is as safe and controlled as a shopping mall, you probably should be reading Krebs on Security more. That's an amusing comparison, given how much of Krebs focuses on offline ATM skimming, copying credit cards at point-of-sale terminals, hacking major retailers's CC databases, and using stolen cards at retail and mall stores to cash them out...

udba 10y ago

I'm currently applying for co-op jobs (internships) and while trawling the university job board I've seen many positions requiring big data this or machine learning that. What's not clear to me is why companies who don't seem to have any need for machine learning team (i.e. a subscription box company) are looking to hire one. Surely part of this can be pinned down to the hype associated with ML that may well die out, but the proliferation of these tools doesn't bode well for Maciej's dream of a weird, creative, and interesting internet.

teej 10y ago
These companies aren't looking for someone to develop new machine learning techniques, they are just looking for someone who can slap together existing utilities to meet their goals. Companies that run on subscription literally live and die by their churn rate. It is both feasible and reasonable for a subscription box company to hire someone to use machine learning to build a predictive churn model. That may seem trivial to you but that's the reality behind those job posts.

chewxy 10y ago

Regarding Maciej's fears about machine learning - I've written about this before, and even right now I'm not sure where I stand exactly, except that tweaking the algorithms to compensate for bias is definitely not the right answer: if you look at the mirror and don't like what you see, you don't draw on top of the mirror to accentuate the result! You go on a diet! I liked the idea of data gardening, but the thought of going-to-communities is daunting. I get tired even thinking about it. Regarding living beyond walled gardens: > Publish your texts as text. Let the images be images. Put them behind URLs and then commit to keeping them there. A URL should be a promise. But people already do that! The question now is to turn to why people do otherwise. I personally do not understand the reason people say, post long blogposts on Facebook, but I do understand for services like Medium. For example, I'm extremely tempted to write on Medium because it provides the network effects of readers clicking on tags to read next. So the question is how do we democratize that?

big_surprise 10y ago
So the question is how do we democratize that? Commenter wtracy has already linked to the FSF's list of High Priority Free Software Projects... From there, look into what they have to say about free wifi (and in particular, but not limited to the OrangeMesh package): http://www.fsf.org/campaigns/priority-projects/free-software-drivers-for-network-routers http://www.fsf.org/campaigns/priority-projects/free-software... If a convincing case could be made that the benefits to National Security outweigh the costs to the copyright cartels, I'd be willing to bet that young secondary-schoolers would have a blast with a decently designed curriculum that includes a working student-to-student mesh-network as one of its goals.
- chewxy 10y ago
  I actually meant democratizing the network effect that Medium has. The "free marketing" bit. I mean, right now one can pretty freely go write up a blog using self-hosted wordpress, octopress, pelican, hugo or whatever. But choosing that over Medium can sometimes mean a lot more work to put in. But if we can democratize the ease-of-use and the good bits of Medium/Facebook/Twitter... Maciej's end statement about "using open standards, write text in text, images in images" would have been achieved. The problem is that corporations now create a significantly more compelling version (in most criteria - UX, UI, etc) of the Free and Open versions out there.

makomk 10y ago

Have to admit that I didn't expect to see that quirk of LiveJournal culture mentioned in an article on the HN front page, let alone in a speech to the Library of Congress. It just sort of faded away without really influencing the current generation of social networks. Also, it's funny how the net changes, how unthinkable it is to have a social network that doesn't slice up people's data and use it to advertise to them now compared to how anti-advertising LiveJournal was back then. Not convinced it's a change for the better.

idlewords 10y ago
I'm the guy who gave this talk. To add to the funny, LiveJournal hired me to rewrite their ad engine in 2007. I did a horrible job at it, but turned my ineptitude into a principled and lucrative ideological stance that I have milked ever since. Don't be afraid to pivot.
- embarcadero 10y ago
  Was this recorded? Link?
  - pauldino 10y ago
    There's a YouTube link at the top of the page. https://www.youtube.com/watch?v=8gcu2GQf7PI&feature=youtu.be&t=5h31m50s https://www.youtube.com/watch?v=8gcu2GQf7PI&feature=youtu.be...
- bo1024 10y ago
  I enjoyed reading it a lot, thank you. I think about these issues a lot and you gave me new things to think about / crystallized some nice perspectives.

pimlottc 10y ago

> Many [programmers] work jobs that are intellectually stimulating, but ultimately leave nothing behind. There is a large population of technical people who would enjoy contributing to something lasting. This hits pretty close to home.

leesalminen 10y ago
Same here. I was just talking with a friend last night about how software developers should have a creed, like how doctors have the Hippocratic oath. We could potentially cause far more harm than doctors nowadays.
- bthdonohue 10y ago
  As part of my computer science program in college, we studied the ACM's Software Engineering Code of Ethics and Professional Practice, which in effect is what you describe. http://www.acm.org/about/se-code http://www.acm.org/about/se-code
  - cmrx64 10y ago
    And as an aside, the ACM is currently collecting comments on revisions to their code of conduct. http://ethics.acm.org/code-of-ethics/code-2018/ http://ethics.acm.org/code-of-ethics/code-2018/
- mamp 10y ago
  Interesting, but note that the Hippocratic Oath doesn't work so well with preventable errors in health care the 3rd leading cause of death in the US https://www.washingtonpost.com/news/to-your-health/wp/2016/05/03/researchers-medical-errors-now-third-leading-cause-of-death-in-united-states/ https://www.washingtonpost.com/news/to-your-health/wp/2016/0...
keyle 10y ago
Same here. I'm battling with this thought a lot. Beyond jobs, I think there should be communities of developers, designers, producers, writers, getting together and figuring out this stuff. And I don't mean open source projects. Let's group together smart people wanting to make a difference and have a hit list of things we (people) actually need. A group that would organise people into mission driven development. I'm so fed up of getting paid to potentially make founders rich. Or to be a small cog in a gigantic machine on a slow decline. I'm also unemployable because I can't buy into the corporate BS anymore. And where I am, there doesn't seem to be design/dev jobs that actually want to make a difference. It's an economy problem. The startup thing seems to be the best way we go about solving problems in the world today. But if you happen to _not_ be at the right place at the right time, meeting the right people, poof, it's gone. I can't imagine that an advanced specie would operate this way. We should be focused on solving problems, instead of being focused on escaping the rat race, to then be able to solve problems. I'm glad I am not alone seeking purpose. There goes a point where you're technically advanced, you have itches to fix things and all you see is the broken economy of consumerism and "let's give kids video clips and smileys, derp".

qwertyuiop924 10y ago

>the Internet is a shopping mall. There are two big anchor stores, Facebook and Google, at either end. There’s an Apple store in the middle, along with a Sharper Image where they are trying to sell us the Internet of Things. A couple of punk kids hang out in the food court, but they don't really make trouble. This mall is well-policed and has security cameras everywhere. And you guys are the bookmobile in the parking lot, put there to try to make it classy. It's already been mentioned, but this guy needs to get out a bit more. The internet is a city. There's the specialist shops (HN), the bustling malls (Reddit, YT), the shady back alleys (4chan, 8chan etc.), the historical districts (Usenet, Archive.org), the cafes (IRC, ICQ, Slack, etc.). To their credit, the author is more knowledgeable than most, however. I see so many dismiss the internet as just Facebook, or YouTube, discuss trolling as if it's a single phenomenon, and it's a recent thing, associated with Social Media. So many think that there's an internet culture: there isn't: there's a set of almost infinite numbers of overlapping, interlinked cultures. I can even map out the origins and historical influences of a few. There are even a few who think that social media sites are good forums of discussion. The poor sods: the Usenet was a better discussion forum than Facebook ever was, and the Usenet's not that great. If you really want to see what the internet is like (that isn't advice for the author: I'm pretty sure the mall analogy doesn't encompass his internet experience, and is merely an analogue I find odd), explore. See it all, in all of its weird, wacky, zany, jokey, serious, offensive, manic, smart, stupid, brilliant, insane glory. I promise you, you won't be dissapointed. People ask me why I'm not on social media. It's because social media is boring. Unlike Reddit, 4chan, and the rest, not much interesting happens. Unlike HN, I'm not likely to be intellectually stimulated, or learn something new. Unlike static sites, I don't get to see that kind of wild creativeness that personal webspace tends to invite in hackers, nerds, and others who know what makes the web tick. I don't want to see what you ate, I don't want to see your cat, I don't want to hear banal details about your everyday life. I want to hear something intersting, new, and original. I want to hear the next Ze Frank, or Tom Ridgewell, or Simon Travaglia, or Steve Yegge, or RMS, or PG, or Ryan Dahl, and you can bet I won't on a site with a signal:noise ratio that high. People also ask why I'm fascinated with the internet. My response is, why wouldn't I be? It's a catalogue of decades of human creativity and interaction. It's open mike night at the largest club in the world, which is also a discussion forum, and a shady back alley, and a convention. It is - to borrow and butcher Sir Terry's words - like being blindfolded and drunk at several different parties at once. But, in what it rapidly becoming the sign-off on my incoherent, long-winded ramblings that are really only tangentially connected to the topic at hand, maybe I'm just totally mad. EDIT: tried to clarify that I wasn't trying to insult the author. Not my intent, but it seemed to come off that way. It still does, but less so, and I prefer not to edit my old content too much. Also, I just checked out pinboard. Pinboard is amazing, and I am impressed. Basically, don't take this as anything more than a tangential, incoherent ramble started by an analogy the author used which I found unrepresentative. Because that's what it is.

Esau 10y ago

"And this time it's not the government, but the commercial Internet that has worked so hard to dismantle privacy." So true.

leesalminen 10y ago

> For the generation growing up now, the Internet is their window on the world. They take it for granted. It’s only us, who have seen it take shape, and are aware of all the ways it could have been different, who understand that it's fragile, contingent. The coming years will decide to what extent the Internet be a medium for consumption, to what extent it will lift people up, and to what extent it will become a tool of social control. I agree completely. This is something we should be cognizant of.

morecoffee 10y ago

Giving up control is harder than the author makes it seem. It isn't so much that you give it up, but that you give _to_ someone else. Picking that someone else is extremely difficult and a wrong choice will destroy your community. Using machine learning on the other hand is a safe bet. It is much easier, I would assert, to write machine learning code to organize data than to curate a community of humans to organize data. The ML approach will do pretty good even if it isn't the best, which is why it's what everyone is switching to. Keeping with the author's example, is it easier to organize erotic fanfic with a computer, or enable a community to do it without spiraling out of control?

crzwdjk 10y ago
For example, it is clearly easier to write a machine learning system to find interesting articles and highlight insightful commentary, compared to using something so crude as a group of people on a website collectively voting on which stories and comments they like... wait a minute...

erichocean 10y ago

> Publish your texts as text. Let the images be images. Put them behind URLs and then commit to keeping them there. I sounds like he's saying ephemeral content is worthless and should be shunned. I, and hundreds of millions of others, disagree. You want a bland, awful, boring society? Easy: make everything you do stick around forever—like a promise. And then watch the world self-police as the lifeblood drains out of it. You'll get…Facebook. No thanks.

idlewords 10y ago
The audience for this talk was people with very large collections they're bringing online. I was trying to encourage them to avoid exotic formats, custom plugins, custom software (shudder) when they put this material online, and make them web accessible. For example, here is three quarters of a PETABYTE of historical American newspapers: http://chroniclingamerica.loc.gov http://chroniclingamerica.loc.gov
- erichocean 10y ago
  Okay, that makes sense. I 100% agree that bringing collections online in exotic formats is a terrible idea.

Asparagirl 10y ago

> I’ve saluted the efforts of Archive Team and the Internet Archive, but their activity is like having a museum curator that rides around in a fire truck, looking for burning buildings to pull antiques from. It's heroic, it's admirable, but it’s no way to run a culture. ...but in the meantime, here's an obligatory and shameless plug for donating to the Internet Archive[1] (tax-deductible in the US), or better yet making a recurring monthly donation so they can more accurately forecast revenue for the year, or better still getting your employer to make a nice big donation to this crucial bit of Internet memorybanks. And as for Archive Team, we're always looking for a few good geeks.[2] Run an instance of the Warrior on spare cloud servers, or help patch and ship code at GitHub.[3] [1] http://archive.org/donate/ http://archive.org/donate/ [2] http://archiveteam.org/index.php?title=Main_Page http://archiveteam.org/index.php?title=Main_Page [3] https://github.com/ArchiveTeam/ArchiveBot https://github.com/ArchiveTeam/ArchiveBot

codezero 10y ago
I've got a VPS sitting around doing very little – what's the easiest way to get started?
- Asparagirl 10y ago
  Run a Warrior! Many flavors available: VirtualBox, Dockerfile, AMI (for Amazon EC2), you name it. http://archiveteam.org/index.php?title=ArchiveTeam_Warrior http://archiveteam.org/index.php?title=ArchiveTeam_Warrior It would deeply unethical for me to point out that you could also run the Warrior on free server space that your company might not notice, kind of like the karmic inverse of a bitcoin miner. Deeply unethical. So I won't mention it.
  - deleted 10y ago
    [deleted]
dcposch 10y ago
The Archive is awesome, but the author's sensationalist description of what they do isn't really accurate. For the most part, archive.org is not rushing in to save stuff that's about to be deleted. Instead they are crawling the web 24/7, patiently maintaining a historical record. Check out http://oldweb.today http://oldweb.today It is amazing

aub3bhat 10y ago

Frankly as a grad student (The kind that the author apparently considers "dim witted"), the entire article is meaningless babbling without any underlying theme. I wonder if the author truly understands "Machine Learning", what are his qualifications? A degree in Art History, and some "programming experience" aren't very assuring. E.g. >> "The names keep changing—it used to be unsupervised learning, now it’s called big data or deep learning or AI" WTF?? The author should enroll in a beginner Machine Learning course on Udacity or Coursera before making philosophical statements about fields he has zero clue about. It seems the only skill the author has is piecing together meaningless arguments that appeals to average HN users incapable of distinguishing between informed opinions and pseudo-scientific rants. Hell at least bad graduate students have to give examinations, read papers and make original contributions that get peer reviewed (otherwise they fail/get-kicked-out/drop-out). Not like this guy who does not understands difference between "supervised" and "unsupervised" machine learning, yet feels comfortable in making "prophetic" statements about machine learning. Also >>> "These techniques are effective, but the fact that the same generic approach works across a wide range of domains should make you suspicious about how much insight it's adding." What does he means by "same generic approach". If we assume he is implying specific algorithms then we have a good "No free lunch" theorem that shows that a single algorithm is not effective across all domains. Now if by "generic approach" the author mean "machine learning" in general then its as ridiculous as saying "Mathematics is effective, but the fact that the same Mathematical approach works across a wide range of domains should make you suspicious about how much insight it's adding." The entire article is filled with "truthiness" and "feel-good" statements, which fall apart on closer examination.

idlewords 10y ago
My degree was in studio art, not art history.
- aub3bhat 10y ago
  Those two are still orders of magnitude closer to each other when compared to difference between unsupervised learning with deep learning.

pcmaffey 10y ago

Machine learning does not have less bias than human researchers. It is simply magnified at scale. And that scale is exactly the state of the internet. There is so much data available to study and understand, that we absolutely need better tools, like machine learning or whatever we want to call it, to help us keep up. Shit's moving faster than our human perception can handle, especially for those who didn't grow up with the internet. Yes the data analyctic tools we have right now are premature— like fast food to our productized minds— but they will improve rapidly, as our taste for quality improves. But sure demonizing the things you don't like is one step on the path to learning what's truly valuable.

coldtea 10y ago
>Machine learning does not have less bias than human researchers. It is simply magnified at scale. Scale differences can and often do lead to qualitative differences. Individual (or aggregate) human researchers are not hooked up in huge services to make inferences and deductions automatically about billions of people. Besides those machine learning tools, beside the huge data sets, are programmed in their general framework by human researchers, and are given weights, constraints, and fine-tuning by them, so they have both kinds of biases. >But sure demonizing the things you don't like is one step on the path to learning what's truly valuable. So, kind of like disparaging via a straw-man a speech that offers detailed argumentation?
- AndrewKemendo 10y ago
  Individual (or aggregate) human researchers are not hooked up in huge services to make inferences and deductions automatically about billions of people Yes they (we) are. It's the same data set. TV, movies, papers, internet videos et al. is all the same biased, labeled data that is being fed (watched, listened to etc...) to machines. You automatically make inferences and deduce things about people based on labeling and training of your brain. You're constantly fine tuning by getting new weights about things through interactions with others and media.
  - coldtea 10y ago

jaywunder 10y ago

I don't think I understand what the exact point of this talk was. Maybe the thesis was stated at the end of the talk when he said that he wishes the internet were more like a city rather than a mall. I think the internet can be like a city, and I think a great example of a place where people with conflicting ideas talk together is HN. Sure HN can be an echo chamber at times. But there's quite a few times when people with differing opinions talk about their different opinions. Also I don't necessarily understand Ceglowski's stance on why we shouldn't use deep learning and should avoid surveillance on the web. I don't take issue with becoming a datapoint in Facebook's web of people because nothing bad has happened or can happen from me giving Facebook my data. When most people speak out about the data that's being collected about Facebook and Google users they say they're "worried about what could happen" but then never list any bad things that they're actually afraid of. The speaker falls to this issue too. Ceglowski says: >I worry about legitimizing a culture of universal surveillance. But then never explains what bad could happen from legitimizing that culture. Maybe I'm completely missing the point of the talk? Please explain what I'm missing if I'm actually missing something.

idlewords 10y ago
The audience for this talk was a bunch of librarians and fellow travelers who are bringing large archives and collections online, often at great expense. I wanted to encourage them to find new, engaged audiences for these collections, rather than fixate on how to analyze them with computers. With regard to the dangers of surveillance, I've made a sustained argument about this in other talks. It boils down to the data being collected having great power to harm people if it is ever put to malicious use, and a lifespan that exceeds that of institutions we know how to run. My beef is not with the surveillance alone, but with the combination of surveillance and permanent storage.
- jaywunder 10y ago
  Thank you for explaining that! The context is meaningful and makes your talk make sense. On the regard of data talking into the wrong hands, I take issue to this argument because it's not a unique problem to personal data collection. Any data could be hacked - bank information, address, whatever. But that doesn't mean we don't use the internet for banking and etc. It means we try to make systems that are difficult to hack. It seems like you'd want data collection not to happen on websites like Facebook and Google, when hacking isn't a unique problem to those websites.

goldmar 10y ago

Thank you for this article. I have really enjoyed your writing style, especially the creative metaphors you're been using :)

dvdplm 10y ago

Idelwords is one of those blogs worth dropping everything you do and just take a deep breath and dive in and revel in the joy of clear thought expressed through clear prose. Love it. Thanks.

TranceMan 10y ago

I have been having similar thoughts for a while: https://news.ycombinator.com/item?id=10937201 https://news.ycombinator.com/item?id=10937201