skysight-inc/HackerNews huggingface dataset:
>Therefore, I believe that companies operating this way should pay a "robot tax";

Well, we have a lot of "robots" in the house. We can listen to music via Compact Disc robots or mp3 iPod robots instead of employing human musicians to play live music. For example, composer Haydn's job was the "on call" music director for the family estate.

We also run take our C++ or Java code and let our personal desktop robots of file systems submit them to compilers to parse and execute the source code. The acts of "cl helloworld.cpp" or "javac hellowold.java" puts many human punch card operators out of work.

The elevator robots with automatic safety doors and algorithmic braking systems replacing elevator attendants manually closing the gates and guiding the elevator to the right floor. Robot freon compressors replacing ice delivery men. Etc,

I don't think people realize the oppressive nature of all the robot taxes we'd pay unless we listed every "robot" we interact with that replaced human jobs.
Band takes you on Epic Journey, if you're ready
Seems like now might be a good time to repost this:

https://medium.com/@somewhere/how-i-learned-to-relax-and-sto...
Yup, typical dramatic headline technique.

Anyway, consumer's hunger increases with productivity increases. In 20 years, when even more robots than we already have are deployed, we will all want more complex, highly integrated stuff, requiring the same amount of employment to produce.

Anyone who doesn't believe me, think back to the days before interchangeable parts. We could live that way today and have lots of free time, but we apparently don't choose to. We have higher standards, want more diverse food, more complex entertainment, cleaner everything, fancier, more decorated houses, vehicles with more features.

Additional robots - on top of the ones of which we already have lots of - won't take away jobs, they will deliver us finer consumer items and health standards.
Funneling more money to a corrupt and incompetent government is not a solution, it is a horror show.

Ignore the ludicrous laws that conspire to hurt all but the largest corporate-fascist entities.
I agree but I would say it's not the poorest families that choose cheap colleges but lower middle-class families. People like teachers, office workers, et. al. who can't afford every college or who have to take out loans to send their kids to college are going to be price-sensitive. The poorest people generally make so little that they qualify for great financial aid without having to do academic scholarships.
I think IMAX achieved a counter-effect of people actually realizing that a VR headset would have a widescreen field of view larger than IMAX could ever have. It's only a matter of time until the big screen, highly immersive theater experience will not be seen as an IMAX.
This is false. The Apple money is invested in other companies.
Startup Seeks to Monetize the Fantasy Sports Side Challenge
Google Acquired Agawi to Try Apps or Games Without Installation
At some point, we will have to accept that a society based on the assumption that everyone should find a full-time job just doesn't make sense anymore. In Europe this is starting to become obvious, as we have high structural unemployment (very high in some countries) in spite of the jobs we keep just for the sake of it. Jobs like gas station operators or supermarket cashiers are mostly unnecessary and just kept because people boycott machines while there is unemployment, telemarketing could probably be banned altogether with everyone being the happier for it if it weren't for the loss of thousands of jobs, etc. This applies even to some intellectually-demanding jobs (not all): speaking against my own interest as professor in a small university, I often wonder if all the teaching we do is necessary when any of my neighbors with a PC is a couple of clicks away from lectures by the top professors at MIT.

At the moment, the collective delusion that we need everyone to work 8 hours a day still stands, although we need more and more patches and stitches to keep it going (artificially-kept jobs, subsidies, etc.) It will soon become obvious for everyone that this has stopped being a valid paradigm, and then we will need to make some deep changes. If we don't want millions of people to starve even in fully developed countries, we will need to choose: either we all share the diminishing demand of working hours (i.e. we work significantly fewer hours a day, which is what has traditionally been done to compensate for the advances in technology) or we just accept that we don't need everyone to work and socially admit not working at all as a valid option, with a basic income. Curiously, both choices are traditionally associated with the political left (although some intelligent right-wing liberal economists, like Friedman, have embraced variants of basic income). The traditional right just doesn't seem to have an answer to this.

I'm personally in favor of basic income. Reducing the working week may work for a while, but as the set of jobs where humans are competitive gets restricted to very high-skill jobs only, it just won't do. As sad as it may sound now, there will be people who won't be able to do any really necessary job better than a machine, and we will need to feed them. Basic income will become a historical inevitability sooner or later.
As a very general trend, things are getting cheaper and time more expensive. Thus, the number of items that are worth reselling on eBay is shrinking.
There's nothing in the article that says they do. They say they get a message from the blood collection agency when they donate and another when their blood is used.

I imagine it works pretty much as you suggested below: each bag of blood is identified with a serial number, the collection agency is alerted when that bag is used, this triggers a message from them to the donor.

Would you be happy with that?
We exported the low standard of living to agriculture dependent economies in the third world and keep them there with free trade agreements.

EDIT: I'm not some ranting nut job

http://www.freetradedoesntwork.com/

IAN FLETCHER: Libertarians simply don't know their history. Take out a $10 bill and have a look at the portrait on it. Alexander Hamilton, founding father and intellectual architect of American capitalism, was a protectionist, and protectionism was American policy from Independence until after WWII.

http://www.huffingtonpost.com/michael-hughes/free-trade-does...
Overhype has always been the enemy of AI/ML, leading to unrealistic expectations, then disappointment, then distrust.

But it might be different this time...
Solid and strong and humming along – here’s Mageia 5
Are you saying that if there are more effective ways of raising money, governments necessarily know about them? I'm on your side with regards to taxing, but governments are slow-moving beasts that are often controlled by ideological moves rather than practical ones.
Or ... we let a considerable portion of humans starve to death and reduce the population
Hi Derek! Nice to see you here!|

I actually already think that earning to give isn't the best path for most altruistic people who would be willing to work anywhere. This is a change of view from a few years ago. The reasons are: i) quite a few people are already very successfully earning to give and need really amazing opportunities to donate to; ii) a rising number of very wealthy people are donating most of their wealth (e.g. Giving Pledge). This means that on the margin we really need more talent to spend these donations well.

What I do think is:
- donating to highly effective charities (e.g. GiveWell recommendations) is a means by which anyone who's got a job in an affluent country can make a truly massive difference
- earning to give should be an option that's at least on the table for altruistically minded folks
- as you say, for people who would really enjoy very high-earning careers they shouldn't necessarily think "well I should do something I enjoy less because what I'm doing now doesn't have much social value." (I shudder when I see high-flying lawyers or financiers quitting and doing non-profit consulting outside their area of expertise). Via earning to give, these people really can have their cake and eat it.
- some careers are dual-benefit - e.g. entrepreneurship can generate huge social value in and of itself, and also be very lucrative
- for young people, the most important thing in the short term if you want to do good in the long term is to build skills, and you often build more skills in for-profits than in non-profits. While there, you should earn to give.

Overall I think that at the moment maybe 10% of the altruistic people who would be happy working anywhere should aim to earn to give long-term. It depends a lot on cause, though - some areas are more money-constrained; some more talent-constrained.
GORUCO 2015 live stream – Gotham Ruby Conference
This is the best HN submission I've seen in a very long time. Really thought-provoking.
We have a similar idea to those communes already, they are called "businesses".
Pay no attention to that pita 50 cm from your computer ;)
I've never understood the software engineering community's desire to call PCREs regular expressions simply because it has similar syntax to "formal" regular expressions.

There is good reason to distinguish the two, since they have completely different characteristics. PCREs may use an unbounded amount of extra memory, and may use exponential time. "Formal" regular expressions take linear time and memory, and can match only the regular languages. They operate completely differently (a regular automation vs. a stack based pattern matcher).

Regular expressions can NOT match HTML, PCREs CAN. Conflating the two is not helpful.
Actually, SENS-like repair therapies would be mass-produced infusions for the most part. They'd be the same for everyone, a mix of small molecule drugs targeting metabolic waste (amyloids, cross-links, lipofuscin, etc) and gene therapies (allotopic expression of mitochondrial genes). Some replacement of stem cell populations most likely, which would be a tissue sample, send to the clinic, get back cells for injection.

If you look at comparable technologies today, autologous stem cell transplant is the most expensive, and you can get that for a few tens of thousands of dollars via medical tourism. Other points of comparison are, say, biologics for autoimmune conditions, which are enormously finicky to mass-produce at the moment and presently run to a few thousand dollars per shot or infusion. They'll get cheaper. Generic drugs, widely produced and past their legal protections, on the other hand cost a few cents to a few dollars for a dose.

For SENS-like repair technologies you're looking at one treatment every few decades if it's very efficient at clearing damage, or perhaps every few years if it isn't.
I had some success with pictures of sofas from a top view, but a lot came out as complete nonsense like "nail" or "light bulb". Seems on at least some patterns it is trained to view things in a particular orientation that you would normally see them in. I imagine that if it did exhaustive rotation searches on a lot of objects the results would often be completely incorrect.
That is, their terminology for this project. In facebook's Bolts framework for iOS they use Task and TaskCompletionSource https://github.com/BoltsFramework/Bolts-iOS#tasks
How can you say that in response to a comment saying that Craigslist made $335 MILLION and doubled revenue year over year? I mean sure perhaps dispute the underlying facts (they seem rock solid to me) but if making $335,000,000 in revenue is somehow the sign of a bubble then... i don't know what to say.
I think that startups where the users are principally people in poor countries is a very promising area for socially minded people to work in.

Startups usually (but not always) generate value for their users in the form of consumer surplus. Because of diminishing marginal utility of money, $1 of consumer surplus in poor countries is worth 10x or more than $1 of consumer surplus in rich countries.

Some examples: Wave (YC alum) is making sending remittances cheaper (taking only 3% rather than 10% like Western Union). $0.4 trillion in remittances are sent every year. Segovia is making benefit payments in India more efficient, so that only 10% in lost in transactions rather than 50% as is currently the case. Both of these in my view have massive social value (and are run by people in the effective altruism community).
The Metaphysical Effects of a Magnetic Pole Reversal
Speaking as an bum student :

Your job security is MORE guaranteed even more than before.

All the online MIT lectures still have a high bar in terms of understanding what they talking about.

You cannot just do quantum mechanics by watching some online videos.

The online materials ( Internet, Forums ), increases the size of your market.

Notice the exponential rise of cost of college education. Its driven because more people are understanding the importance of studying in Uni. You will be surprised by how many people in the world still do not know basic arithmetic, and are still growing potatoes.

Its the american idea that winner takes all but that is very false.

Its about raising the average.

If we took a time machine and transported you 200 years in the past your worth to society would be of less importance since people would think you are a crazy person or a witch.

As no one would understand your work, notation, etc.

This is why as more and more of the 3 billion people that still operate outside of the mainstream economy enter it the value of the people doing average work in the mainstream economy increases.
Google Improving Chrome for OS X Performance to Better Rival Safari
Javascript/Meteor
The Popular Vote Is a Bad Idea
Always coming back to this silliness:

> They all float the idea of basic guaranteed incomes for everyone, or tax credits to supplement low-wage workers.

Yeah, just like tractors made 90% of farmers permanently unemployed and they decided to take early retirement and spend time on the beach. It's so disappointing to see otherwise smart people ending up with these kind of conclusions.
Ah, thanks. I hadn't noticed that post was from the OP.
It wasn't your questions that bothered me, but your ideas expressed in these posts: https://news.ycombinator.com/item?id=9744910 https://news.ycombinator.com/item?id=9744929

Your initial question was perfectly fine to me.

Further, while i think HN is inconsistent at best in how it applies its rules², i realize that dang does have a point and i could've dug further with questions, to see if your mind could be changed. However, the same applies to you just as much. Instead of accusing me of being a child³, you could just as well have asked why i recoiled in horror and thus rerail the discussion in a constructive direction, like to3m did: https://news.ycombinator.com/item?id=9745547

--

² The rules are hilariously strict, which can be a good thing, but applied to only a small percentage of rule-breaking posts.

³ Not that i particularly care.
I tried Wolrfram ImageIdentify with a bunch of bicycle photos and it insisted on identifying them as "Bicycle Saddle".

I kept trying different ones and it kept identifying as "Bicycle Saddle"...
This article would not come as a surprise to anyone who works with ConvNets. Sadly, that might not the case for those outside of the field, largely due to media's inadequate coverage of our advances (but this is common outside our field too). No one in the field really believes ConvNets see better than humans. They are very good single glance texture recognizers. It's as if you flashed an image and looked at it for a split second without giving yourself a chance to look around and take some time to gain any higher-level scene understanding. If you tried this with this image you might also think you had seen a leopard. Another point to make is not from modeling side but from data side. If in the training data the leopard texture is highly indicative of leopard, then the ConvNet will learn to strongly associate it as such. As the article mentions, a quick hack would be to make sure that your training data contains many leopard-textured items of different classes. You might then expect the ConvNet to seek other features to latch on to and become less reliant on the texture itself.

Also, we carried out an experiment on ImageNet and the outcome was that "One human labeler (me, incidentally) with a fixed amount of training and a slightly-above average determination reached ~5% top-5 error on a subset of ImageNet test set". The media sees this and it immediately gets spun to "AI now Super-Human. And we're all going to die." It makes a lot of us cringe every time.

Many people in Computer Vision now consider ImageNet "squeezed" out of juice - we're good at texture recognition and when an object is in plain view, and we're now searching for harder tasks and more dynamic range with respect to human performance, in areas such as harder 3D/Spatial tasks, Image Captioning, Visual Q&A, etc. The hope is that these harder datasets might in turn guide us in developing models with more nuanced understanding.
Agents of Empire: a dazzling history of the 16th‑century Mediterranean
Just to be sure, Wolfram Alpha Image Identify was correct, down to it was a particular type of sofa.

https://www.imageidentify.com/result/1ixb9603m9ix1
I'm planning to launch a lead management SaaS for WordPress GravityForms
Hi guys, I'm planning to launch a lead management SaaS for WordPress Gravity Forms. Any input will be helpful.
Stop Per-Person Swimlanes
I think that's a really important concern. At 80,000 Hours when we encourage people to earn to give we ensure they're embedded in the effective altruism community, take things like the Giving What We Can Pledge and so on - mechanisms by which to ensure that our future selves don't fail to live up to our ideals.

It's also worth bearing in mind that the rate of people becoming disillusioned when they do direct work in charities also (anecdotally seems to me) to be very high. Reason is that it's often very hard, often you don't feel like you're having much of an impact. Whereas if you enjoy working in the lucrative career you're in, the 'sacrifice' of donating even 50% isn't really that great, so it's potentially easier to continue in that path. I'm genuinely really unsure which has the greater dropout rate: earning to give, or direct charity work. If I had to bet I'd say it was direct charity work.
That would be passive-aggressive abuse. Unemployment is rarely a choice, yet society likes to make the unemployed feel that way. This would add insult to injury.
Governments are well-known to use every trick in the book to get more money.
NOTE: It's the first time I see the code.

Actually, `fact`, `should`, etc. seem to be macros, as provided here:

https://github.com/jcouyang/ru/blob/master/macro/ruspec.sjs#...

And following lines. It is a bit of syntactic sweetness over a preexisting testing framework. And I'm not convinced that they should be macros.

Unless sweet.js does something really original, macros are generally not first-class. You can't pass macros directly as parameters to functions, for example. I'd rather use macros to allow for nicer function call and attribute access syntax, in general, instead of special casing tests.

After taking a closer look at the language, I have some doubts. As of right now the language seems to be a random set of features that the author found cool implemented as Sweet.js macros, with the rest of JavaScript syntax unchanged. It would be a library in a Lisp world, even in Racket I don't think this level of functionality would be enough to justify writing a #lang.

At least two of the implemented features shouldn't be macros: into and fact/should because they then become second-class objects. You can't, for example, use `into` as an argument to `map`. Shorter lambdas are fine, personally I feel that the `=>` syntax native to JS is enough for this - but that's a matter of preference.

All in all, it looks like a very early attempt and there's still much to implement and improve. Have fun with this, OP! :-)
Hey all, we sent a Pull Request 2 days ago to the author of the Benchmark, as they used OrientDB incorrectly. Now OrientDB is the fastest in all the benchmarks, except for "singleRead" and "neighbors2", but we know why.

We are still waiting for the Arango team to update the results...
Turkish Red Crescent does that too. It works.
Functional Programming Workshop in JavaScript
The real problem here is government and not "private" (corporatist) prisons who would only exist as they are because gov't enabling.

Were we to abolish gov't and it's geographic monopolies on law and policing, then truly private prisons would both be way less common and nothing at all like what's talked about in the article.

Some of the statistics on crime are outdated but Benson's The Enterprise of Law is a great book to look at understanding the problem here.

Conditions were so terrible before the move for privatization in federal prisons (sometime in the 70's). With a move back toward that system (which would never happen because more politicians' and bureaucrats' pockets are being lined) you might not have quotas and the push for continued prohibition from this one little angle, but gov't is not a business[0], so the comparison to private hospitals or electric companies is faulty.

[0] https://www.youtube.com/watch?v=kqoBZLSm1WA
I'm a bit confused. The paper states:

"We have disclosed our attack to GnuPG developers under CVE-2014-3591, suggested suitable countermeasures, and worked with the developers to test them. GnuPG 1.4.19 and Libgcrypt 1.6.3 (which underlies GnuPG 2.x), containing these countermeasures and resistant to the key-extraction attack described here, were released concurrently with the first public posting of these results."

Basically that Libcrypt 1.6.3 underlies GnuPG 2.x. But when I check my system:

foo@bar:~$ gpg2 --version
gpg (GnuPG) 2.0.22
libgcrypt 1.5.3

So I'm wondering why GnuPG 2.0.22 isn't using Libgcrypt 1.6.x?

I can see from your reference that I can upgrade to Libgcrypt 1.6.x but that it requires a rebuild of GnuPG, which I'd rather not deal with right now.
After rotating the image 90 degrees, the predicted result changes substantially. The author should not be surprised. A convolutional neural network is translationally invariant, not rotationally invariant.
No. The idea that your voice is being recorded and sent to Google is something that a lot of people might not want.
Achievement: Bronze Blood Donor (10 donations)

Achievement: Super Hero (10 lives saved)
Let's say I didn't want to use the ImageNet or CaffeNet pre-trained models but wanted to train my own model (say, of thousands of images of sofas, leopards, jaguars, and cheetahs); are there any tutorials that walk through the process of building a CNN on your own data?

(I've seen the comments like https://news.ycombinator.com/item?id=9584325 and watched the lectures and youtube walkthroughs, but they're all theoretical and I'm looking for documented code to go along with that theory)
You could get something like 10% of the karma of an article if you upvoted that article before it reached the frontpage and that article gets more than a certain threshold (say: 100 points, which would somewhat mean that the article is good. That way you get some of be benefits of the submitters, but not all. A bit like being an early employee at a startup.

However, people could just upvote all the newest articles without reading it and get the karma from the ones that end up scoring well, so that system wouldn't be perfect.