I'm not moving from Textmate to Emacs or Vim - <AUTHOR> http://smartic.us/2008/12/21/i-m-not-moving-from-textmate-to-emacs-or-vim

<comment><USER2> _Lisp is interesting in its own right, but I want to be able to configure my editor in the language of my choosing._

The Lisp is not the bottleneck. The problem with reconfiguring your editor is that you have to learn the API. That's a bunch of work, no matter what editor or language you use. It's not as if your extensive knowledge of Ruby means you can just sit down and start pounding out extensions for your editor.

The difference between the 2+ _N_ hours you will spend mastering Lisp + the Emacs API and the _N_ hours you will spend mastering the TextMate API becomes less and less important as _N_ grows larger.

I gave Textmate a serious try partly because I was curious, and one of the things I was curious about was: How great would it be to be able to configure my editor in Ruby, a language I really like? And the answer was: About ten seconds worth of great. I sat down to try to figure out how to do it, and took my first look at TextMate's API, and before I could even get into it the back of my brain spoke up: "Why are you teaching yourself the API to some proprietary software when you could be learning the equivalent-but-free emacs API, which is classic and was thought out by some fairly smart people and has a pile of very good free documentation and an awesome development environment called 'emacs' and which you won't ever need to learn more than once?" And that was that.

</comment><comment><USER3> Most of his reasons sound stupid, maybe im just biased(because i love vim) but his list of textmate problems was much more concrete and to the point than the vim one. So vims problems are that its cryptic, its not a complete picture and it requires you to learn a language to script it. Those sound absurd reasons, i think he is just trying to find himself reasons to ignore textmates problems, which is not that bad, i do the same with vim(emacs is uncomfortable and elisp is retarded, textmate is proprietary and runs only on the mac...)</comment>


How popular can Lisp documentation be? - <AUTHOR>

<comment><AUTHOR> <http://lispdoc.com/>

Lispdoc, a search engine for Common Lisp documentation, is always going to be about as niche as a site can get. But it gives me something to hone my skills on and stops my brain from turning to mush while I wait for my Green Card.

I've been putting some more effort into it recently. I'd be interested to know if people here have suggestions for what I could improve. Please feel free to consider no nit too small to pick.

Some stats:

Lispdoc responds to around 3000 searches per day on average.

Its Google page-rank is 4/10

Alexa rank is 568,856 (three weeks ago it was 1,130,856. current 1 wk avg is 228,583)

A Google search for 'lisp documentation' puts lispdoc in 7th place.

<comment><USER2> hey bill :-)

"I've been putting some more effort into it recently. I'd be interested to know if people here have suggestions for what I could improve. Please feel free to consider no nit too small to pick."

cltl2?

lispdoc is a great resource, btw

<comment><AUTHOR> hey nick,

cltl2 is definitely a good idea - in fact I think that's what I should do next for sure. Thanks!</comment></comment></comment>


Hreflang - <AUTHOR> https://en.wikipedia.org/wiki/Hreflang <comment><AUTHOR> Large parallel corpus is essential to good machine translation. hreflang allows one to build large and diverse parallel corpus by crawling the web.

If you are publishing multilingual contents, consider adding hreflang support. You may help future machine translation for your language pairs without much effort!</comment>


Dear Google Recruiting... - <AUTHOR> http://www.daemonology.net/blog/2014-01-27-dear-google-recruiting.html <comment><USER3> I don't understand why it bothers people so much to be contacted by recruiters. I just send a quick reply that says "I appreciate the interest, but I'm not looking for new position right now.". It takes me about 10 seconds to type that sentence and hit send. It takes me such little time that I probably would not remember if they contacted me again a year later.

I'm always grateful to have skills that are in demand. I have friends in other fields that are not so lucky. No need to be the girl that tries to tell everyone how attractive she is by complaining about the attention she receives from guys.

<comment><USER4> > I don't understand why it bothers people so much to be contacted by > recruiters.

It likely depends on how big your online footprint is. I've been on the Internet publicly since 1989 and hence you can find me all over. That also means recruiters do. I have no problems with the ones who are good at their jobs, but about half are below average, working on commission, and their tactics are the same as spammers (spread yourself indiscriminately far and wide). Many are downright scammers such as taking resumes off the net and then pretending to represent those people, or scraping job postings off websites and then pretending to represent those companies.

At the top of my resume I put a "note to recruiters" that makes it clear what I am good for. It is very clear then which recruiters have made even that miniscule effort, versus just started spamming right away.

I'd say I see about one good recruiter for every 20 spammers. And that is what is bothering. Even worse the lack of response or saying no doesn't deter the spammers so you have to do something about it. I made a blocklist in the end.

[http://rogerbinns.com/recruiters.html](http://rogerbinns.com/recruiters.html)

<comment><USER5> > but about half are below average

> I'd say I see about one good recruiter for every 20 spammers

These two seem contradictory, but the second statement strikes me as much more true than the first. Recruiters in this industry seem to be more parasitic and less knowledgeable than even real estate agents, and I say that with great hesitation. Any job where the attracting principle is "ooh money, and I don't even need to know anything!" is probably not usually a service that's worth a damn.

<comment><USER6> Statement 1 is tautologically true.

<comment><USER7> No. Consider the sequence (2, 2, 2, 10).

<comment><USER8> The "average" is not a technical term in statistics. It's a shortcut in everyday speak for some measure of centrality. What you're referring to is (probably) the arithmetic mean, but the average can be any other measure (for example, when you talk about "average speed" you're not using the arithmetic mean, but the geometric one), including the median.

Also, in this case the mean and the median are probably close to the same thing since recruiter skill is likely to be normally distributed, but that's a different story. </nitpick>

</comment></comment></comment></comment></comment></comment><comment><USER9> Dear Colin,

You're extremely lucky to have talents that are highly sought-after and well paid. I know many talented architects and designers with experience who just scrape by. Just ignore Google's recruitment advances and move on :)

<comment><AUTHOR> _Just ignore Google 's recruitment advances and move on_

If I thought I was the only person being annoyed by them, I would probably do this. But I've spoken to lots of other developers who get similarly annoyed by Google recruiters despite their attempts to tell Google Recruiting to stop contacting them -- so I figured it was worth writing a "ha ha only serious" public piece in the interest of getting Google's attention and maybe saving a lot of developers that same occasional irritation.

<comment><USER10> > I've spoken to lots of other developers who get similarly annoyed by Google > recruiters despite their attempts to tell Google Recruiting to stop > contacting them

It might have been worth mentioning this in your post.

As it stands, the faux-formal structure, slightly melodramatic tone and repeated references to your cushy career situation make it read like a classic humblebrag.

<comment><USER11> He doesn't need to be humble. Google would be extremely lucky to have him. Let's stop wasting time pretending that he's lucky to be contacted by them, or that he needs to be careful about how he presents this. He's at the top of his field. Get over it.

<comment><USER10> I'm not questioning his ability or professionalism.

I take issue with the fact that the stated intention of his post - to get Google's attention and prevent similar incidents in the future - is at odds with the tone of his writing. That's all.

<comment><AUTHOR> The intended tone of my writing is "funny enough that someone at Google might notice and do something about this problem". Sorry if that didn't come through.

<comment><USER12> It comes through just fine. It's possible your detractors have just had the good fortune of not experiencing the 'pesky recruiter' problem, Google or otherwise. You can take heart in the near certainty that, if they work in the technology field at all, they will.

</comment></comment></comment></comment></comment></comment></comment><comment><USER11> Dear Every Recruiter That Has Called Me In Last Couple Years,

I know you think you can help me find awesome Rails programmers in the Chicago area or whatever kind of developer it is you think you're great at sourcing, but all I can think of when you call us to pitch your services is that my company's name is going to end up in a blog post like this.

Go to hell,

Thomas.

</comment><comment><USER8> Given Google's emphasis on quantifying every aspect of recruitment, I wouldn't be surprised if the reason is because their numbers show that contacting people who previously rejected offers was more likely to result in a hire than contacting people who never interviewed, and that they decided that ignoring "do not contact" instructions was worth it after some time. Basically, kind of an retargeting strategy but applied to hiring. I understand why this may be annoying to you, but your case is probably rare enough that they decided to go along with it -- I would think that most people do not care enough about being contacted by companies they do not want to work for to complain. I do not condone this but the assumption that you may not feel as adamant about not working at Google as you did two years ago (during which a lot can happen) seems perfectly understable to me.

With that said, your post does come across as really obnoxious. Asking to have an "ON PAIN OF DEATH" mention added on their file? Really? I dislike having my instructions disobeyed as much as the next guy, but if I counted properly this is _6 emails over more than 7 years_. Surely one could live with receiving one unwanted email every year or so? It's not like it's that hard or time consuming to just ignore a message or to decline politely -- after all, a lot of people do it multiple times on a daily basis, and I'm sure you do too.

This is too bad, because the tone of your post distracts from the perfectly valid (but IMHO, minor) point that this policy does imply things about Google they view themselves.

</comment><comment><USER13> I like being contacted by Google. I'm not really interested in interviewing with them ( long process, doubt I'd pass, would have to move ) but it makes me feel good that the top tech company (YMMV) in the world is interested in hiring me.

<comment><USER14> This isn't a knock on you - I was contacted last summer. Had a long chat, but didn't pursue it, as I'd have to move. That wasn't the only reason, but a primary one. To me, I had about 5 minutes of feeling valued, then the cynic in me started thinking that they must be scraping the barrel to contact me. I don't mean it in a self-loathing "i suck" sort of way, but... they must be tapping out 'locals' already to be reaching out across the country. They really can't find anyone else within driving distance who's at least as qualified as me?

</comment></comment><comment><USER15> Disclaimer: I used to work at Google and have some incidental knowledge of Google's recruitment practices but am not an expert.

Many of Google's recruiters (especially the sourcers who are looking for candidates) are temporary contractors.

These contractors generally have a tenure measured in weeks and they are vying for one of very few full time positions. This high turnover, low institutional knowledge, and desire to distinguish themselves would be my best guess at explaining why the "Do Not Contact" note is not being respected.

<comment><USER16> This is what I figure as well. Sourcing and incentive structure Google has in place for recruiting naturally gives "do not hire" note won't be respected. It's a problem that needs a systematic solution, but probably not worth the cost to fix it.

<comment><USER17> Get an agent, if you're that in demand you can hire somebody else to handle your recruiting and opporunitites for you?

</comment></comment></comment><comment><USER18> Dear OP

Yes you have the right to not be contacted by Google if you don't want so.

But may I advise you to not get pissed by the fact that your labour force and intellect is being greatly demanded. Disturbance apart, you should be thankful.

<comment><AUTHOR> I don't mind recruiters contacting me. I mind recruiters contacting me _when the file in front of them tells them that I 've specifically asked them to not contact me_.

</comment></comment><comment><USER19> I understand being annoyed that they ignored your request, but would it really lessen your recruiter spam by an appreciable amount? I get such random requests, eliminating a single company wouldn't make much of a dent.

I've just gotten good at hitting shift-3 or e (depending on my mood) in gmail the second I sniff recruiter in an email.

<comment><AUTHOR> It's not the emails which bother me; it's the fact that they're ignoring explicit instructions.

<comment><USER20> How do you solve this for recruiters other than Google? Surely you must be getting a lot of traffic from them too....

<comment><AUTHOR> I can't think of any other company which has had recruiters continue to contact me after I've replied "nope, not interested".

</comment></comment></comment></comment><comment><USER21> You could have just solved the problem by taking a job at Apple, Adobe, Intuit, Lucasfilm, or Pixar!

</comment><comment><USER22> Dear Google... ignore these dilettantes. I'll bend over as far as you want. Holla.

</comment><comment><USER23> I also turned Google down after interviewing [1]. They contacted me every six months to see how I was doing. Eventually, I asked them not to contact me again, and they haven't.

Other recruiters haven't been so nice, but it's important to remember that recruiters are people too. Their jobs can be very stressful, since much of their compensation comes from successful hires. I ended up writing a rather conciliatory post, and I link to it whenever a recruiter contacts me: [http://geoff.greer.fm/2013/10/23/dear-recruiter-please-do- no...](http://geoff.greer.fm/2013/10/23/dear-recruiter-please-do-not-contact- me/)

It has been quite successful. Replies from recruiters have been understanding and pleasant.

1\. One cool thing about Google: They asked me to do a post-mortem to talk about out why I turned them down. I met a manager at a coffee shop and discussed my reasons. He also wanted to make sure that the interview process had been enjoyable for me, and asked for feedback on what they could do better. I was impressed by their thoroughness.

<comment><AUTHOR> _They asked me to do a post-mortem to talk about out why I turned them down._

I had the same experience, although for me it was a web survey rather than a face-to-face interview (probably because I wasn't local). Whether they actually paid attention to what I told them, I'm not sure; 99% of the problems in the interview process were due to my recruiter screwing things up, but she got promoted a few months later.

</comment></comment><comment><USER24> I totally understand why this is annoying and can sympathize. However, it was probably a mistake to write a blog post about it and put it around. Not because of any backlash against your future prospects or because you're now missing out on some opportunity, because that's not your problem.

I just think that by writing this in the way that you have, you've tarnished your personal reputation. If you're fine with that, then no big deal. But from this article and reading up on you, I know objectively that you are very intelligent and extremely accomplished in your chosen field, have a skill-set that is in constant demand, and are somewhat foolish.

If I were to complain about a problem almost no-one in the world shares, I would do it privately. This public complaint is particularly worthless since your complaint is likely not going to have an impact on whether or not some temp recruiter at Google will try to hire you in 3 years.

So, it doesn't accomplish much for you, and it convinces a whole bunch of people that you don't appreciate what you have.

<comment><USER25> The problem isn't _that_ uncommon. Google recruiters truly carpet bomb the market (as defined by LinkedIn, it seems) with introductions.

I only got them off my back after stating (twice) that I have a life and as such won't move ~10 timezones for a job.

</comment></comment><comment><USER26> What a jerk. I thought once of using Tarsnap.. now I know there's no way I'll ever use or recommend this product. Ask a support question about Tarsnap? Bam, blog post about you annoying the shit out of him with your question.

If you are not interested in an e-mail, it takes about a third of a second to press "!" in gmail.. that's a free way pass to the spam folder. But the person sending the email, the recruiter, won't know it. So a quick: "No thank you. I'm more than busy right now and not interested in new job opportunities" would do wonder.

And FYI, the last time a google recruiter tried to recruit me, we had a very nice chat about my own startup (Hacking Health) where we pair technical talents with health professionals to find innovate solution in healthcare. These guys are very well connected and can introduce you to so many people.. So, if you think it's okay to be jerk to them, then realize that you're closing the doors to great opportunities by doing so.

<comment><USER11> And now we know how much your recommendations about secure backup software are worth. Thanks for sharing.

<comment><USER26> >> secure backup _software_

The software isn't the problem - it's probably great - it's the _service_ that I wouldn't recommend.

<comment><USER11> I don't even understand what you're trying to communicate anymore. "The software's great! But don't ever use it!"

</comment></comment></comment></comment><comment><USER27> I wish I had problems that resembled this. :(

</comment><comment><USER28> I doubt the time it took you to write this is less than the amount of time it would take to simply ignore their emails.

<comment><USER11> Said every spammer ever.

</comment></comment><comment><USER29> They seem to cast a wide net as far as their recruiting efforts goes. I kinda wish they put more effort into identifying unexperienced hires as well, as I remember expending quite some effort to try to get hired by Google after I left graduate school, but to no avail. Now I have shown my quick ability to learn (which was already proven by my education) in the world of development and now I get contacted...and I don't know whether I want to work for Google anymore.

I deeply question their talent identifying apparatus. Even worse for them, if they did a correct analysis, they probably would have saved a lot of $. It would probably take over 2x what I am making now to woo me over, and that's not necessarily guaranteed.

<comment><USER19> Why didn't you just apply? I imagine that a recommendation from a current employee would boost your chances, but I don't think a recruiter contacting you changes anything over just a resume submission, at least not at most companies.

<comment><USER29> I did before - multiple times.

</comment></comment></comment><comment><USER14> When google asked for my resume (which... oddly enough, they already had because that's how they said they got my contact info), I told them to bing for it. Haven't heard from them since. Perhaps that'll get them off your back in future.

</comment><comment><USER30> This guy is so full of himself

<comment><USER31> It's very rare I say this, but he has every right to be.

</comment></comment><comment><USER32> Hmm, I've had variable experiences with Google Recruiting.

I had one experience which was very good, with a Google Engineering team - <USER2> didn't end up passing through - but they made the experience fun (good questions), and they were very gracious hosts.

I had another with a Google Sales team in Australia - where they made me do some four-page online assessment, answer more questions - then booked me in for a phone interview at 09:00 - then emailed me at 17:00 the day before to cancel.

Their reason - oh yeah, the years of experience we required has changed...

</comment><comment><USER33> It's just insulting when recruiters don't do basic research on the people that they contact. Yeah, it's not the worst problem to have in the world, but I get the feeling that a lot of these people are just spamming anyone they can find in a particular keyword and then expecting those people to do the recruiter's job for them.

</comment><comment><USER34> as a girl on okcupid, I fully understand this.

</comment><comment><USER35> People seem to be missing the crucial point here.

It isn't that they keep ignoring the "DO NOT CONTACT", it's _why_ Google wants his services so badly in the first place. What does Tarsnap do?

Think about it. Google wants to be bullet proof. Probably internally at first, but then maybe roll out the benefits to other services.

<comment><AUTHOR> I highly doubt any of the recruiters who have contacted me know what Tarsnap is.

</comment></comment><comment><USER36> I can't see a good reason for posting the names of the recruiters in this post, and can't see why this is that "special" of a case. Maybe if they called that many times, it would be legitimately annoying. But a few spam emails? I don't know many people who would emotionally react like this.

</comment><comment><USER37> Imagine a world in which Google recruiters have a profile of you on their desk of likes, dislikes, likely life goals, and potential avenues to woo you into joining them. I imagine Facebook has a dataset that could be applied to make such a thing and soon (if not already) so will Google.

</comment><comment><USER38> Why's this post even up? He just needs to get a bigger inbox and learn to use the archive button.

</comment><comment><USER39> Is Google unique in this? Or is this a generic tech company/recruiter problem?

<comment><AUTHOR> Google is the only company I've found which seems to be unable to take no for an answer. I get lots of recruiter spam from hedge funds, but I don't think any of them have ever re-contacted me after I've told them not to.

</comment></comment><comment><USER40> so google contacts you every couple years. must really clog up your inbox...

</comment><comment><USER41> Eh, I've been contacted by them too. Probably a large portion of the HN audience has. It's called throwing out a big net, it's not like they're personally begging you.

</comment><comment><USER42> I was contacted by a Google recruiter recently and have a phone interview set up now after a phone screen. Until I read this I was feeling pretty pleased with myself :(

</comment><comment><USER43> WoW you are publicly complaining about Google trying to recruit you?

Have you read how people treated this guy [http://valleywag.gawker.com/startup-stud-hates-homeless- peop...](http://valleywag.gawker.com/startup-stud-hates-homeless-people-ugly- girls-and-pub-1150802451) or this guy [http://valleywag.gawker.com/happy- holidays-startup-ceo-compl...](http://valleywag.gawker.com/happy-holidays- startup-ceo-complains-sf-is-full-of-hum-1481067192).

IS your goal to be label yet another arrogant/ignorant tech douchebag? That just might now happen!

</comment><comment><USER44> on the bright side: enduring the unimaginable suffering which this horrific indignity has obviously caused you, will strengthen your character.

</comment><comment><USER45> #Humblebrag

</comment><comment><USER46> Now you can ask them to add a link to this post. "DO NOT CONTACT but if you still think you should, please check this link".

</comment><comment><USER47> as a front-end engineer I have just been abducted to work in a hiring war room at my company (30 FTEs in 30 days is the mandate)

seeing and having to do what sourcers do for the last week has been eye- opening. identification, assessment, and engagement of skilled candidates is super hard and very time consuming.

I have nothing but sympathy for these people now...

</comment><comment><USER48> If only Steve Jobs were around, he would put the industry cabal back in place and fix this problem for you pronto.

</comment><comment><USER49> Isn't this spam you can report because it's illegal? If not what's the difference?

</comment><comment><USER50> Every considered working for Google? I hear the perks are great!

</comment><comment><USER51> so obnoxious

</comment><comment><USER52> I think about my friends from high school and college who are struggling to find meaningful work when I read things like this. I try to imagine what it be like from their point and it comes off like an entitled prima donna is complaining about being recruited by what one of the coolest companies on earth. Honestly I think as an industry we should try to keep some perspective here.

<comment><USER5> To me it comes across as the reverse of sour grapes: "Oh woe is me, I'm being solicited by diamond salesmen to add extravagant adornments to my golden palace. Can't they just understand that my platinum plated safe contains more diamonds than they could ever offer? Why is life so hard?"

<comment><USER53> see also: #humblebrag, #whitegirlproblems

</comment></comment></comment><comment><USER54> This is beyond a First World problem

<comment><USER55> How about a "First Percent Problem"?

While I agree with the sentiment, I also agree that if Colin is repeatedly asking the company not to recruit him, they should respect that (and should have the first time, too).

Perhaps if he puts a time limit on it, that will make things more clear (e.g., "Do not contact me for 100 years").</comment></comment>


Ggplot2 Book: Springer Publishing Agreement (2014) [pdf] - <AUTHOR> https://github.com/hadley/ggplot2-book/blob/master/springer/contract-2.pdf <comment><USER2> If my legalese is up to scratch, the contract appears to entitle Springer to charge the author for copy editing on top of everything else. Why shouldn't the author hire a freelance copy editor and distribute the book himself through an on-demand printing service?

</comment><comment><USER3> I loved the Ggplot2 when I used it several years ago. But at the time (not sure if it's still true), I found this book _essential_ to understand how to use the library beyond the simple examples.

This github repo is interesting because it has so much stuff -- even the contract with Springer and a textfile about marketing strategy. Seems like the author wanted to be as super transparent as possible.

Not sure if that's why it was posted here, but cool in any case.

</comment><comment><USER4> Some are critiquing the 18%. As someone who has authored a technical book with a similar caliber publisher, I can confirm that it's on the generous side. Though typically there would be some form of book advance (few k) and copy editing included as well.

The thing is, the the technical literature industry is kind of like venture capital. Publishers will throw a lot of things against the wall and whatever sticks will net them enough of a return to cover the rest. It can cost upwards of 50-100k to produce a book and most of them tend to flop. It's really hard to understand which ones will flop as well, unless you have intimate domain expertise and can judge the technology and the community around it as well. At that point however, you may as well write the book yourself.

</comment><comment><USER5> Maybe OP could explain what might be interesting about this contract?

<comment><AUTHOR> Have you seen a real book contract? I haven't.

<comment><USER5> No, and I have no baseline for comparison.

<comment><USER6> Now you have a baseline for future comparisons, isn't that interesting?

<comment><USER5> Maybe if I had read it!

</comment></comment></comment></comment></comment><comment><USER7> > 18% share of revenue for the author of this tech book ...

What kind of system of commerce is it, when the stars and the accomplished fall to ruin, rent and low-cost bus passes, while coffers swell to record size, and abusive money lending , addictive drugs and casinos prosper standing littered by the wreckage of their victims.

Maybe paperback books were more of a treasure than we realized ? .. including the livelyhoods of the participants ? Is there one person or player or style to blame for the aggregation economies that are consuming its citizens, farmers and aspiring creators mercilessly ? USA here.

</comment><comment><USER8> 18%

<comment><USER9> 18% is way more than usual. Royalties for printed tech books are usually 10-15%. Which is bad anyway.

<comment><USER10> We got 6% from Springer for a textbook (6% total split between the authors, not per-author) [1].

However we were first-time authors, and also insisted that we be allowed to leave the "author version" PDFs online as open access [2]. So it's possible the lack of a fully exclusive contract made our royalties lower.

[1] [https://www.springer.com/us/book/9783319427140](https://www.springer.com/us/book/9783319427140)

[2] [http://pcgbook.com/](http://pcgbook.com/)

</comment></comment></comment><comment><USER11> No money down?</comment>


What does it mean for a machine to "understand"? - <AUTHOR> https://medium.com/@tdietterich/what-does-it-mean-for-a-machine-to-understand-555485f3ad40 <comment><USER3> This is a good balanced article that gets a lot of things right. We should take a forgiving approach when we talk about AI systems. And as the author points out the problem is not that AI systems dont have understanding yet. The problem is with the hype which leads many to believe that we are close to building systems which can understand us.

That said, I have a small problem with the examples presented to say that already machines understand us :)

The article says 'For example, when I tell Siri "Call Carol" and it dials the correct number, you will have a hard time convincing me that Siri did not understand my request"

Let me try to take a shot at trying to explain that Siri did not "understand" your request.

Siri was waiting for a command and executed the best command that matched. Which is, make a phone call.

It did not understand what you meant because it did not take the whole environment into consideration. What if Carol was just in the other room. A human would maybe just shout "hey Carol, Thomas is asking you to come", instead of making a phone call.

If listening to a request and executing a command is understanding, then computers have been understanding us for a long time. Even without the latest advances in AI.

<comment><USER4> So the next version of Siri can locate Carol's phone in the next room and will just beep her phone to tell her to see you. Of course that's still not understanding.

The classic analogue is of course the Chinese room argument: [https://en.m.wikipedia.org/wiki/Chinese_room](https://en.m.wikipedia.org/wiki/Chinese_room)

<comment><USER5> Which is an absolutely textbook example of begging the question.

If you could make a machine pass the Turing test it might be intelligent - <USER2> no one has, and it's debatable if it's even possible, and it's even more debatable if, hype notwithstanding, the Turing test is even a good test of human-equivalent intelligence, because it ignores side channels that are fundamental to human communication, including tone of voice, posture, and facial expression.

(Yes, people communicate over email/SMS. But no one communicates over email/SMS without an implied social context that hugely limits and simplifies the content of any conversation.)

It's not the "call Carol" problem that needs to be solved. It's the "understand the entire world context well enough to know _how_ to call Carol without being told - which includes being able to research information that isn't already available, and also includes edge cases like 'We went to Carol's funeral last week' and 'Carol had her phone stolen yesterday' and 'Carol is flying to Australia and won't be receiving messages for another 12 hours" and "Carol prefers FaceTime to WhatsApp."

And so on.

Ultimately your toy machine has to show evidence that it understands the entire world and can learn about it like a human can - which includes being able to do original research that isn't a simple literal Google search, parse humour, understand emotional responses and common cultural references, and follow standard social protocols.

That's a _much_ harder problem than having a vaguely plausible limited text- only conversation, whether it's in Chinese, English, or Swahili.

<comment><USER6> I would call the moving goalposts a subtle sign of a win as well if it is getting closer that previous "unthinkable" tasks need more qualifiers. Missing or adding them makes it easier or harder. To be a smartass anything can pass a text messages from the comatose (that is nothing) and nothing can reliably "prove" itself god by say resurrecting and teleporting your dead relatives to you would be obviously useful but impossible as that isn't something text messages can do.

</comment></comment></comment></comment><comment><USER7> I have a straightforward definition of "understand". To understand means to be able to give a (representative) example of the (intensionally) given set. Though it is harder than it seems, as it usually means solving the constraint satisfaction problem.

For example, take the classical AI knowledgebase fragment, "bird is animal that flies". If I ask example of bird, it can say "eagle", and exhibit some understanding. We can then probe further and ask for a bird which is not an eagle. If it says "bat" or "balloon", it exhibits that it still doesn't understand birds quite right.

In particular, if the description is nonsensical and thus impossible to understand, we cannot give any examples.

This idea was really inspired by the study, where they asked people to recognize nonsensical and profound sentences, describing certain situation. The profound are the ones where you can create a concrete instance of the situation.

<comment><USER8> Then animals do not understand.

You've rigged this up to operationalize it for current digital machines.

"Understanding", "Intelligence", etc. is a feature of animals in their environment. We need to begin there; and that _is_ what we are talking about.

We "understand" how to drive as a dog "understands" how to play fetch. Understanding is not ever going to be a trivial rule that some digital system may instantiate.

It will always require direct causal contact with an environment. In my view "understanding" is "competent play in a changing environment" \-- ie., the ability to modify the environment _as it changes_ in accordance with your goals.

This rough definition is inspired by work in animals to understand the role of the neocortex, and animal learning, and the role of consciousness therein. Roughly: consciousness is "perceptual and cognitive intelligence grappling with environmental change".

<comment><USER7> > Then animals do not understand.

I am agnostic regarding that, as I don't think there is any evidence that they do not attempt to build models that are consistent representations of reality.

I am assuming, based on my own experience, they also have this "internal lightbulb" going on when they think they have built the correct model. But whether they are actually cognizant of it (self-aware), I have no idea. (I guess what I am saying is that understanding and self-awareness are two different things.)

<comment><USER8> I'm not even talking about self-awareness. I'd be happy to raise the bar to that level when (, if) we have mice-level AI.

However the bar is way below that at the moment, and masquerading as "intelligence".

Current machine learning (ie., mere statistical) approaches to AI, that do not explicitly aim to dynamically model environments/goals/behaviour/etc., aren't even meeting an extremely minimal notion of intelligence.

We have at the moment "smart rocks". Electrical current "tumbles down" a "digital mountain" and we all it's path "smart" because it has useful outcomes. Equally, a rock rolling down a hill finds an optimal path -- it aint "smart".

We should look at what the rock does when you start adpating its environment: eg., create a little dip in the mountain side; it gets trapped. A mouse doesnt get trapped in a dip, it continues to explore -- why?

Because animal behaviour is inherently exploratory of the enviornment. A mouse doesnt "solve" a maze, it intelligently navigates it -- so that when unexpected change occurs, it isn't "broken".

At the moment, all AI systems _radically_ break when such changes occur -- because they are statistically trained on mere data. They arent dynamically model building. They aren't in an environment. They're just rocks rolling down a hill.

</comment></comment></comment></comment><comment><USER9> On the one hand the quote by Edsger Dijkstra comes to mind. "The question of whether machines can think is about as relevant as the question of whether submarines can swim." We are hardwired to attribute great significance to what happens both in our own head and that of other people.

On the other hand, machines still perform actions that one could call 'stupid'. When alphago was losing in the fourth match against Lee Sedol it would play 'stupid' moves. These were, for instance, trivial threads that any somewhat accomplished amateur go player would recognize in an instant and answer correctly.

Humans, and also animals, have a hierarchy in their understanding of things. This maps on brain structure too. Evolution has added layers to the brain while keeping the existing structure. In this layered structure the lower parts are faster and more accurate but not as sophisticated. Stupidity arises because of a lack of layeredness so when the goal of winning the game is thwarted the top layer doesn't have any useful thing to do anymore and it falls back on a layer behind that. For alphago pretty much the only layer behind its very strong go engine is the rules of go. So, even when it is losing it will never play an illegal move but it will do otherwise trivially stupid things. For humans there is a layer between these things that prevents them from doing useless stuff. For living entities this is essential for survival. You can be forgetful of your dentist appointment but it is not possible to forget to let your heart beat. It seems that this problem could be mended by putting layers between the top level algorithm and most basic hardware level such that stupid stuff is preempted.

<comment><USER10> > When alphago was losing in the fourth match against Lee Sedol it would play > 'stupid' moves. These were, for instance, trivial threads that any somewhat > accomplished amateur go player would recognize in an instant and answer > correctly.

I think this behavior is less 'stupid' than it appears. When human beings play Go, the points matter even to the loser, and everyone goes home when it is over. There is life outside of Go. To Alpha Go, Go is it's entire universe. Part of the way it was trained was competing against other instances of itself, a sort of Thunderdome where the loser doesn't get to continue existing, and doesn't contribute to future generations. To Alpha Go, defeat is death. The behavior we observe when losing is nigh-certain has a human equivalent, we call it desperation. Alpha Go is trying moves that can only possibly work if the opponent makes a catastrophic blunder, which is incredibly unlikely, but it's the only shot it has.

</comment></comment><comment><USER11> > When I ask Google "Who did IBM's Deep Blue system defeat?" and it gives me > an infobox with the answer "Kasparov" in big letters, it has correctly > understood my question. Of course this understanding is limited. If I follow > up my question to Google with "When?", it gives me the dictionary definition > of "when" — it doesn't interpret my question as part of a dialogue.

Google Search doesn't, but Google Assistant does. I posed the exact queries suggested by the article and the second query of simply the word "when" did give the correct answer (May 11 1997).

<comment><USER12> That example seems pretty unrelated to what I would think of as "understanding." That's more just a feature request for Siri.

It's like saying "my calculator lets me type '1 + 2 =' and gives me the answer '3,' so it seems to understand that question, but when I look at the calculator I see there's no 'sqrt' button that would show me the square root of 3."

The fact that my basic calculator doesn't have a "sqrt" button is pretty irrelevant to how well it "understands" how to add two numbers together.

<comment><USER13> Your basic calculator still has a concept of context, though. If you go '1 + 2 =' then it will give you '3', and if you press '/ 2 =' then it will give you '1.5'. It 'remembers what you were talking about' within its very limited scope.

I think what they were trying to get at is that understanding is stateful.

</comment></comment></comment><comment><USER14> I don't remember where I first saw it, but the best definition of "understanding" I've seen is "being able to encode and compress".

For example, imagine a system that has as input the picture of a human face in RAW format. If the system runs the picture through JPEG compression, for example, and returns something substantially smaller, it has shown some understanding of the input (color, spatial repetition, etc).

A more advanced system, with more understanding, may recognize it as a human face, and convert it to a template like the ones used for facial recognition. It doesn't care about individual pixels anymore, or the lighting, just general features of faces. It understands faces.

An even more advanced system may recognize the specific person and compress the whole thing to a few bits.

I would say that an OCR scanner understands the alphabet and how text is laid out, GPT-2 understands the relationship between words and how text is written. And a physics simulator understands basic physics because it can approximately compress a sequence of object movements into only initial conditions and small corrections.

Lossy compression makes this concept non-trivial to measure, but it's still a world's away from the normal philosophical arguments.

</comment><comment><USER15> > Speaking as a psychologist, I'm flabbergasted by claims that the decisions > of algorithms are opaque while the decisions of people are transparent. I've > spent half my life at it and I still have limited success understanding > human decisions. - Jean-François Bonnefon's tweet (as quoted in > [https://p.migdal.pl/2019/07/15/human-machine-learning- > motiva...](https://p.migdal.pl/2019/07/15/human-machine-learning- > motivation.html))

<comment><USER16> The advantage of humans is that we have a building bullshit generator.

If someone ask why you like ice-cream, you can tell a nice story about the hot summers during your childhood, but the reality is that sugar and fat are very useful.

If a the autopilot of a Tesla hit someone, the error report is "Fatal error 0xDEADBEEF: coefficient 742 > 812".

If a person hit someone the explanation is "It was dark and near a curve. I was texting that is totally safe. I got distracted by reindeer nearby. And I snoozed and was thinking about reaching a handkerchief".

</comment></comment><comment><USER6> To be gadflyish do humans even truly understand or do they just claim they do because they had the observations roughly encoded from what they have been taught? Teachings which themselves often include unfounded assumptions or outright superstition.

Human understanding has been wrong often enough, missing enough crucial context to be dangerously hillariously wrong even amongst the "experts" of the day who came closest.

The isn't some epistemological nilhism but to point out that understanding is incomplete for everyone and just because a given intelligence subset doesn't match with our assumptions doesn't mean it is wrong - although it also isn't always right.

</comment><comment><USER17> I think getting near human level for NLP understanding means be being able to visualize and combine all of the dynamic systems that language represents. I mean it's obvious that you can get pretty far just by processing a lot of text, but there is a limit. Some information about the way things work just is not encoded very well in text the way it is in video input. So you need to be able to do a sort of physics simulation for starters. Except it can't just be physics, because there are a lot of patterns that occur that you need to be able to call up and manipulate or combine that are not just plain physics. These patterns are not represented in text.

There are projects doing video and text understanding. I think the trick to efficient generalization is to have the representations properly factored out somehow. Maybe things like capsule networks will help. Although that my guess is that to get really sort of componentized efficient understanding neural networks are not going to be the most effective way.

</comment><comment><USER18> The proposal in the article is to define "understanding" and work towards testable satisfaction of the definition.

This sounds a bit like a studying for a test taking. What if we made a definition and then worked successfully to reach the state when, according to this definition, the system "understands". Can we expect to be satisfied with the result in general, outside of the definition?

The definition of understanding could be tricky, as history suggests. Other than "to understand is to translate into a form which is suitable for some use", there could be many definitions. Article itself brings examples of chess playing or truck driving which were considered good indicators, yet failed to satisfy us in some ways.

Maybe we should just keep redefining "understanding" as good as we can today, and changing it if needed, and work trying to create a system "good", not necessarily "passing the test"?

</comment><comment><USER19> OK, wow, the old guard sure knows how to write sensibly. This is a great article.

But I have to disagree with this (because of course I do):

>> For example, when I tell Siri "Call Carol" and it dials the correct number, you will have a hard time convincing me that Siri did not understand my request.

That is a very common-sense and down-to-earth non-definition of intelligence: how can an entity that is answering a question correctly not "understand" the question?

I am going to quote Richard Feynman who encountered an example of this "how":

 _After a lot of investigation, I finally figured out that the students had memorized everything, but they didn't know what anything meant. When they heard "light that is reflected from a medium with an index," they didn't know that it meant a material such as water. They didn't know that the "direction of the light" is the direction in which you see something when you're looking at it, and so on. Everything was entirely memorized, yet nothing had been translated into meaningful words. So if I asked, "What is Brewster's Angle?" I'm going into the computer with the right keywords. But if I say, "Look at the water," nothing happens – they don't have anything under "Look at the water"!_

[https://v.cx/2010/04/feynman-brazil-education](https://v.cx/2010/04/feynman- brazil-education)

In this (in?) famous passage Feynman is arguing that students of physics that he met in Brazil didn't know physics, even though they had memorised physics textbooks.

Feynman doesn't talk about "understanding". Rather he talks about "knowing" a subject. But his is also a very straight-forward definition of knowing: you can tell whether someone knows a subject if you ask them many questions from different angles and find that they can only answer the questions asked from one single angle.

So if I follow up "Siri, call Carol" with "Siri, what is a call" and Siri answers by calling Carol, I know that Siri doesn't know what a call is, probably doesn't know what a Carol is, or what a call-Carol is, and so that Siri doesn't have any understanding from a very common-sense point of view.

Not sure if this goes beyond the Chinese room argument though. Perhaps I'm just on a diffferent side of it than Thomas Dietterich.

</comment><comment><USER20> Does AlphaGo 'understand' go?

I think the key ingredient is 'being in the game', that means, having a body, being in an environment with a purpose. Humans are by default playing this game called 'life', we have to understand otherwise we perish, or our genes perish.

It's not about symbolic vs connectionist, or qualia, or self consciousness. It's about being in the world, acting and observing the effects of actions, and having something to win or lose as a consequence of acting. This doesn't happen when training a neural net to recognise objects in images or doing translation. It's just a static dataset, a 'dead' world.

AI until now has had a hard time simulating agents or creating real robotic bodies - it's expensive, and the system learns slowly, and it's unstable. But progress happens. Until our AI agents get real hands and feet and a purpose they can't be in the world and develop true understanding, they are more like subsystems of the brain than the whole brain. We need to close the loop with the environment for true understanding.

<comment><USER21> If the Agent would 'understand' Go, we'd expect it to adapt to a round board easily. Humans probably would. (argument from Gary Marcus)

<comment><USER20> Even a simple scaling down of the board from 19x19 to 9x9 has a huge effect on strategy. A circular board would probably produce something that doesn't look like Go and would confuse trained humans as well.

</comment></comment></comment><comment><USER22> To understand means to classify, to modelize.

</comment><comment><USER23> You should direct the question to the computer if you want a meaningful answer.

</comment><comment><USER24> Self consciousness is required for understanding and intelligence

<comment><USER25> Self consciousness can be equally stratified and broken down functionally. It's not a boolean either.

</comment></comment><comment><USER26> I'm with John Searle on the Chinese room [1] opinion, i.e. that a machine cannot be said to "understand" language even if it is able to pass the Turing Test. That is because when we say "understand", we are referring to particular kind of human experience (qualia?) that a machine simply doesn't seem to have, but animals, for example, do.

[1] [https://en.wikipedia.org/wiki/Chinese_room](https://en.wikipedia.org/wiki/Chinese_room)

<comment><USER27> I can say that _you_ don't have qualia and you can't prove me wrong.

Does that seem _dangerous_ to anyone else?

I also don't see any distinction between "qualia" and "soul" other than spelling, but perhaps it's because _I_ don't have one.

Finally, I have this question for Searle: Say you understand English. Does any specific neuron in your brain understand English? No, the larger system of neurons+neuronal connections does, so why doesn't the system of grad student+book understand Chinese?

<comment><USER12> Dangerous? No. To me it just seems to mean that "qualia" is not a particularly useful concept, particularly when discussing the capabilities of computer software.

<comment><USER28> The issue is that we're using a word based on human mental activity and social agreement and then applying that to a computational process in a machine, which likely leaves out part of the human experience which makes up the word understand.

It's more accurate to say the Chinese room computes results which humans recognize as successful translation from English to Chinese. The understanding is all on the side interpreting the output.

<comment><USER12> Then what is the point in asking if a machine "understands" English and Chinese? It sounds like the question would be either completely untestable, or the answer would just be "no" by definition because we're defining "understanding" to be "based on human mental activity." It just doesn't seem like a useful question if the answer can not be determined by a test such as the Chinese room thought experiment.

<comment><USER28> Well, if we asked this about Data from Star Trek, then the answer would have to be yes, or mostly yes (Data does struggle to make sense of some human behavior on the show). So then the question is what gives Data an understanding that the Chinese Room lacks?

Data participates in human society and he has a human-like body. Data also has subjective experiences, as evidence by his dream sequences in one episode. Whereas the Chinese Room is just following a bunch of rules for translation. But Data doesn't merely translate from one set of symbols to another given a large set of rules. He learns by interacting with people and his experiences as an android. From that we could say understanding is the result of an embodied social activity that the Chinese Room completely lacks. Whatever the Chinese room is said to be doing, that's not the same as understanding language.

Another way to put it is that language isn't equivalent to symbol manipulation, even though it makes use of symbols, or a least since the written word was invented.

</comment></comment></comment></comment></comment></comment><comment><USER29> I don't think it's possible for machines to understand. Numbers are meaningless, our human actions give them a useful function. All of the meaning a computer appears to provide is the preassigned values of layers and layers of programming work done by humans. Even today AI has a lot of human tagging and categorization that makes it useful.

The idea that a new self- sustaining meaning generation can arise out of the interlocking mechanisms of a computer is an interesting one. As we see self driven car CEOs describe some of the most advanced systems we have, requiring to be run in controlled environments and balking at the infinite complexity of real life, are we really building computer systems that are anything more than an incredibly sophisticated loop?

<comment><USER30> Well, what does it mean for humans to "understand"? Don't humans understand things by altering the state and connections of neurons in the brain? You could make the argument that the brain is also an "incredibly sophisticated loop".

My point is that humans are also highly-sophisticated, biological machines, so if you say machines cannot "understand", you are making the same claim for humans as well.

<comment><USER29> Humans also squirt fluids around in their brains. Brains as machines is one of many ways to think about humans. Humans can conceive of and move past thoughts or concepts that would cause a machine to crash. I think more ideas describe human brains than being simply machines, though that idea is useful in places.

Making the claim about what a human is in the absolute, is more about what you fill the unknown with than the nature of a human.

Understanding is the difficult question. I would argue the understanding people want out of machines is the ability to generate, use and self-manage tools and that the machine knows the tool's place or context under a human value, story or intent and adapt to the implications of that higher order. That in the most exaggerated sense would be perceived as a machine that understands, but of course people mean different things when they say that.

<comment><USER31> Are you equating machine here with "sequentially programmed computer?". Because computers and neural networks specifically have gone far beyond that.

<comment><USER29> I get how ML works. I don't mean loops as a for(int i) loop, but the concept of a loop itself, a circle. A self-driven car with ML decision making is still bounded by some rules we will be forced to compromise on. Some people at MIT are focusing on deaths per miles driven as a safety metric to determine whether we can replace humans with ai cars and when that might happen.

But given the constraints of ML/ai you will eventually have a bounded container where an ai car can operate and where it can't. The car will be tasked with looping through that environment from job to job then back to recharge at it's base station. For all the sophistication of getting the car on the road and working it won't really be making up it's own story through the world nor will it understand the greater context of it's actions. The pattern recognition in CV is great, but it is fed by humans, so the meaning that a tree should be avoided has been initially put in by a programmer, even if the car in the moment chooses to avoid the tree by itself. The car is crunching meaningless numbers like a pipe directs water.

So when people say a machine "understands something" it can't ever really be true because all of our machines don't know what is going on in the world, they only know what numbers they see and how to behave when those numbers change. At the very bottom it's electricity looping through logic gates and that same principle is repeated all the way up to a car that loops through it's environment and comes back.

If all the humans left the planet, the car wouldn't be described as understanding the world, it'll be seen as a generic device sitting in a garage somewhere waiting for orders from a human. If you fill the earth with aliens the CV breaks not having seen aliens before, the roads get changed over time by nature, the high detail mapping it relies on fails. The cars "understanding" only exists as an outcome of electric impulse. It doesn't understand and never could. We are building more and more sophisticated loops, and I'm glad, but to think computers can understand is a doomed project. They will never "get" the values, intents and stories we put in them. Computers will forever be a labour of love is not able to regress into understanding what we mean it to be.

<comment><USER16> > _A self-driven car with ML decision making is still bounded by some rules we > will be forced to compromise on._

The atom in the molecules in the neurons of your brain are bounded by the laws of Physics. They can't disobey them, they are as free as the coefficient of the ML tables.

> _If all the humans left the planet, the car wouldn 't be described as > understanding the world, it'll be seen as a generic device sitting in a > garage somewhere waiting for orders from a human._

Unless some car have setup an alarm to go to pick you from work at 5pm, you are not there but it goes anyway. After some time (1 hour?) it gives up and return home to get charged and wait for the next day. The waiting time depend on the weather (if it is cold or rainy) and the battery charge and perhaps the congestion of the roads.

Once per year they go to the robot-mechanic for the anual service. They also go when a tire or something get broken. They can call the autonomous crane in case it is needed. During the repairing time, they call a replacement and send all your info and schedule, so you would not miss your appointments (in case you were still there).

The car also negotiates automatically the insurance with the company web service, and pays the registration fees. Your autonomous house pays the electricity bills. Until your bank account is empty.

If you have some money in a good investment found this can last for a long time, until your car is too old and decides to retire and buys a replacement.

We are still very far from this scenario, but it is not so difficult to imagine that a bunch of small features compose nicely.

Somewhat related: [https://en.wikipedia.org/wiki/Hachikō](https://en.wikipedia.org/wiki/Hachikō)

<comment><USER29> I like your hachiko characterization of a patient and loyal car. That level of automation would be nice, I find cars to be a chore sometimes.

What I'm trying to get at is deeper. I guess it's a question of philosophical form. Can you grow an software package to the point of transcending a looped format? Usually a program has our goals and desires established in the coding process and we may through in some qualitative checking functions. We then compile it into a binary form that runs on a CPU that has a clock. That CPU always runs, and the human relevant meaning in the code like function names, the human interpretation of images, video, maps and sound was evaporated only leaving streams of binary. The binary flows through logic gates that act like plumbing tools. The tools can check their own output and proceed down different qualitative paths.

ML as a form grinds out the problem of optimizing the path through those logic gates against qualitative checks. Then we store the working model and loop it at runtime.

So why can you give a human the idea 'making cars can be sold and get you laid' and the human will change their entire career, living location and lifestyle to suit a better economic output, but the program cannot reason/create a form that is not a loop?

If we give a car body sensors and body 'brains' it can synthesize many different perspectives at once. Tactile door handles could give fingerprint/heartbeat/temperature senses on the human driver, as one tiny example. You could program in assumptions about what a high temperature human needs and wants. You could give the car every kind of imaging sensor, air quality sensors, moisture level sensors. You could track and synthesize all that data across time and evolve in a sense for when it's going to rain like ants have, or whatever. It could 'feel' the world. But it would still be that sheepdog waiting at home.

Could it anticipate your needs? Only as a historical projection and whatever you program in. Can you infer human intent, thought or value from sensors? Computer vision applied to human faces or voices? I don't think so.

Humans use different forms of language to transmit intent, values, stories, feelings. The idea that we could have a language or sensor inference that we talk to the car with that will perceive and adapt to the conflict our own mind is wrestling with and seeks to solve is difficult. Google's automated hair dressing appointment booker is cool, it is extending the breadth of voice commands a computer can respond to without having to understand what the words mean or the conflicts implied in understanding their meaning but only how they should be plumbed around as electric bits.

I guess the endless hope is that we just have enough quantity of processed information we can build a machine that you can interface with, it'll solve the problem and that you don't need to know how the innards of the machine work. Which always seems like a plausible goal until it isn't. Web apps break, the internet can behave unpredictably, washing machines require cleaning and soap/ washing knowledge, cars break. Stuff that can be ignored is usually because we pay others to fix the problems quietly. Shifting the burden of understanding how to deal with looped quantative machines to the capatalist/currency system, another quantative system.

The challenge of allowing a human to ignore the new loops one must learn the structure of and thus be able to say the machine 'understands' me instead of I having to understand it, is a forever doomed hope that we benefit from trying to solve.

<comment><USER31> Just bring it down to the basics. Our brains operate on neurons, neurons operate on physics, physics can be fully simulated by computers.

This looping, CPU, "programming it in", and app concept are not the direction machine learning is going in. That's not how deep learning and neural networks work. You can integrate them with an app and do looping yes, but you can also just connect them to each other. No looping, no "programming it in", no apps.

<comment><USER29> Our brains don't solely work on neurons. There was a neuroscience video with 3-4 prominent people in the field dispensing of the idea that brains are computers. They squirt fluids around, it is an unknown. There are plenty of things about existence that physics does not capture.

Frankly I'm not saying ml is programmed in, only the initial conditions are, which is where the meaning is. We have hired a lot of low income earners to classify images for image recognition, which is the outsourcing of discerning meaning from the CPU to the he human. These kind of broad discussions don't go anywhere here, I should go somewhere more philosophical.

<comment><USER16> Fluids in the brain carry a few hormones from here to there and the distribution of neurotransmisors have an important role, but they act very slowly. If we ever have a 100% bug compatible model of the neurons of the brain, adding the flux in fluids will be easy. They can be modeled with a very low number of slow changing variables.

I don't expect to see ever a 100% bug compatible model of the brain. I expect to see some system that does a somewhat similar calculation and produce results that look similar to the result in the brain. Something like the eye and a camera.</comment></comment></comment></comment></comment></comment></comment></comment></comment></comment>


Show HN: Mind, a flexible neural network in JavaScript - <AUTHOR> http://www.mindjs.net/

<comment><USER2> I was intrigued. But a couple of things:

      - the movie poster breaks as soon as it should start predicting your score
      - an option to skip movies you haven't soon would be helpful
      - it showed me a movie I had already rated in its initial data gathering phase

I'm interested in playing around with this even after a rough demo

<comment><USER3> Attention to detail is important here. One definition of an "intelligent" system is one that does not appear "unintelligent".

One big issue for me is that I know very little about some movies and I don't want to offer an opinion about it.

<comment><AUTHOR> 100% agree. Really appreciate the feedback! I added a skip button. I'll work on the missing poster issue too :)

<comment><USER2> Cool. I starred the repo on github so I can follow your progress. I might have a use for this in a project of mine and I like the API you've established

</comment></comment></comment></comment><comment><USER4> I wasted time rating about 60 movies - not a large data set mind you - and it predicted I would rate _Spirited Away_ as a 1 star. I imagine because I rated most other "Animated" and "Adventure" movies prior to it relatively poorly.

 _Spirited Away_ has been my favorite movie since I was a child. So I had a slight chuckle about the prediction. :)

That's _expected behavior_ for how the network was trained, so it's not meant as criticism.

I'd love to play with neural networks more but lack the creativity to apply them to something interesting...and what I'm really interested in training them on is far beyond my abilities.

</comment><comment><USER5> looks neat; will mess with</comment>


E. B. White, the Art of the Essay No. 1 (1969) - <AUTHOR> https://www.theparisreview.org/interviews/4155/the-art-of-the-essay-no-1-e-b-white <comment><USER2> When will The Paris Review run interviews with leading bloggers and other online-first writers?

This is important because they are missing the vast swathe of content that is produced in this day and age. I wouldn't be surprised if 80, 90, or even 95 of written content was digital only these days.

All in all, I think it is time for The Paris Review to interview a writer who is known primarily for their online-only content.

I find it interesting that many of the established literary magazines still haven't extended the definition of literature to capture blogging and tweeting as new forms of media.

They do a good job of including journalism, comedy writing, poetry, and short fiction. But they never extend their interviews to new forms of online-only or online-native writing.

Is there is any justification for stopping the definition of literature short of blogging, tweeting, Tumblr'ing, etc?

There are two that come to mind. Firstly, that The Paris Review considers these forms of media too new. I, of course, understand that it takes a while for the establishment to feel comfortable with new things. But, honestly, online media isn't that new anymore. It was new 20 years ago, but certainly not today.

Secondly, perhaps someone might say that online media is mostly functional and non-creative -- or that it's not a forum for creative media. Surely, that is true for much online writing -- but so is it true for offline writing.

Finally, it feels funny to say that creative writing can exist on some platforms, like Twitter. But, why? Because they are short-form? Doesn't that still give writers the room to produce hyperconcentrated creative forms? Haiku are short -- are they not creative, and worthy of the term 'literature'?

<comment><USER3> Can you name any bloggers or tweeters you think they should interview?

Remember this is the Paris review. They arn't really looking for pop culture stuff. They interview people people who already have some level of academic acceptablitiy. They've done them with R. Crumb and Chris Ware. I'm sure they'd interview a blogger if they found someone they were interested in.

<comment><USER3> Adding to that ... I'm sure the'll do 'The Art of Memes' with someone in 20 years. But not yet. How many late career tweeters and bloggers do we have?

</comment></comment></comment><comment><USER4> It's interesting that when White delved into his journals from years past, searching for facts, he only found opinions, thoughts, ideas - hot air. All that hot air must have felt urgent and important at the time.

Might have lessons for all of us.

</comment><comment><USER5> For anyone curious (as I was), here is the cover of the New Yorker with the seahorse White painted in 1932:

[http://www.condenaststore.com/-sp/The-New-Yorker-Cover- April...](http://www.condenaststore.com/-sp/The-New-Yorker-Cover- April-23-1932-Prints_i8563040_.htm)</comment>


Bitcoins: the Free Lottery that uses CPU cycles for virtual cash? - <AUTHOR> http://radoff.com/blog/2011/06/03/bitcoin-mining-free-legalized-lottery/

<comment><USER2> "As an experiment, I've attached a script to my website to generate some Bitcoins using the spare cycles you have available while visiting this website".

CPU 100% on both cores, fans started up. Some feedback on your experiment: I didn't like it.</comment>