skysight-inc/HackerNews huggingface dataset:
Borrowing from Iaian Banks' Culture universe, where aliens that are pretty much relatable as Earth humans (they're humaniform, even DNA-compatible reproductively, just not from Earth) are designated "1.0" on a sapience scale. See [1] for a discussion of the difference between sentience and sapience. An entity well below 1.0 (Banks never specified, but reading between the lines it felt like 0.5) is considered sentient, but not sufficiently sapient to achieve self-awareness. Personally, I'd prefer a scale that goes negative, to establish a bright line test that accommodates for example, Downs Syndrome patients.

We probably can claim 0.1 or 0.01 on such a scale.

Interesting and left too undiscussed IMO are the economics of productizing what currently goes under the AI umbrella. It is so expensive, and such a big task to automate with even the shard of AI we pursue today, that the numbers in many (though not all) cases don't seem to pencil out unless the benefits can accrue to a few dominant oligopolic providers, from nearly all human-staffed positions where each individual position is largely dominated by a single low-cognitive skill repeatedly applied. But interestingly, lots of physical tasks are left alone, which seems to point to a weakness in that economic model: despite joking talk of the coming robot apocalypse upon jobs, human jobs that require diverse physical and perceptual engagement with the environment are nowhere near common automation.

I see this in a lot of domestic household chores that have yet to experience disruption at the hands of AI. That's at least a 50M-count global market population willing to spend say, $2500-10000 USD per year on a robot that can in the beginning perform the housekeeping chores a hotel housekeeping crew routinely performs for every room. Be trainable on a per-item type basis to put up dishes and cutlery the same way into a dishwasher and back to storage, fold clothes and put them up, and mow the lawn: all highly-repeatable tasks that are only addressed by single-purpose, very expensive "AI solutions" today, tell me that if you are investing into any kind of general-purpose AI, invest long-range, like Uber-scale "point a money-hose at it" long-range.

[1] http://www.rebekkahniles.com/2012/03/word-box-sapience-vs-se...
how people waste their time. imagine someone thought this was a sound idea to do it like this >.> and approved it for a big media outlet. this is like those "science proves cats are nice because 20 people like cats" articles >.<
Get a job. A master's degree in CS will help to augment your experience in the industry - it won't obviate it. I would recommend taking a look at Georgia Tech's OMSCS program, which (for non-CS undegrads like myself), necessitates some number of years of professional software engineering experience.
Do you think they also like creating a new identity to hide behind when they say something they suspect will clash with who they usually pretend to be?
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I didnt mean to imply they didnt put work in! Sorry if I did.
Those three letters don't seem to mean anything any more. What the hell are you talking about?
(Removed before you folks flag it and ban me)
I agree with everything you said except one bit.

> In my experience, someone who refuses or takes offense at a well-framed coding exercise is probably not going to be someone you want on your team.

In my experience those who refuse are the top of the top. We adapted our interview and intake process to accommodate these people (usually with a more stringent and goal oriented probation period), and it was the best thing we did in terms of resourcing. The people we took on through this stream ended up being by far the best performing bang for buck employees. They are opinionated and snobby, but that's a good thing, because they actually care about their respective fields enough to have strong opinions. They don't waste time with tests and coding challenges.
Authors seem not know about this work: https://pdfs.semanticscholar.org/ff7b/3a7b1dad73797ff7c79ac2...

One of the claims in the fine paper that started the discussion is that there's a need to perform several flips at once to find better solution. The paper I cite does something very similar - it walks along chained variables postponing flips until energy lowers for sure.

They also claim their solver has O(vars) time complexity for many problems, including ones with high density (clause/variable ratio). But nothing revolutionary.
Skew-T log (p) for the common pilot
Yep, the thing big clients are buying from big law firms is their liability insurance, not their super-unique law expertise.
He forgot the largest problem with hackintosh - running unsigned code from an untrusted developer. Who’s to say what’s in that Clover boot loader binary or the random Kexts you need to install? As a toy, it’s cool, but anyone doing anything sensitive (banking, coding for profit, etc) is taking risks that are completely unnecessary.
Agh I typed up a response but it got deleted somehow. But basically, I view there as being 3 layers of understanding. For whatever level you're stuck at, there's different ways to get "unstuck".

1. Understand the task they're solving, how they did it, and their results. Anybody with a basic understanding of the domain should be able to do this by reading the abstract/intro and conclusion. If you find yourself having trouble here, you probably just need more background in the field.

2. Gain some intuition of why their method works. This is probably one of the hardest parts to figure out how to do, and is probably the part that most people stumble on. Really, this is basically the entirety of what you're trying to do when you learn math. There's also varying levels of intuition. There's "I get why this might work", "I get why this works", and "I get why it's impossible that this doesn't work", in order of difficulty. The more background you have, the easier this intuition is to grasp. Alternatively, you can bootstrap your intuition by reading other people's blog posts, talking to somebody who understands the paper, asking the authors, playing around with your own implementations, etc. I'm not sure anybody has any good answers for this stage. Personally, I really like good blog posts from bloggers I know are good, but unluckily, many papers do not have blog posts attached :(

3. Finally, there's the strict mathematical rigor part. These levels aren't really strict; oftentimes, I'll treat math I'm not familiar with as a black box theorem. If you don't have the math background for these proofs, there's usually not much better recourse than learning the subject properly.

Luckily, many ML papers barely have any mathematical proofs :)

Alex Irpan has a great explanation of the Wasserstein GAN paper here: https://www.alexirpan.com/2017/02/22/wasserstein-gan.html

If you're looking for interactive blog posts, distill.pub probably has the best: https://distill.pub/2017/research-debt/

And one final note: Many papers (especially papers that aren't math papers) are often surprisingly simple to get to step 2; it's just hidden behind a lot of cruft. I will say that it's wise to be careful about so called "intuitive explanations" of a concept. If somebody gives an "intuitive" explanation for why X is true, but that intuitive explanation doesn't explain why !X is false, it's not very useful.
At least you get people to think about their behaviour.
Avoiding shell injection in Ruby, Phython, and PHP (2008)
Why Is In-House Embroidery Digitizing Costly?
I think this is a good perspective. I also think talking about the top 1% is unhelpful and obscures the picture in a different way. Most of the top 1% are remarkably rich compared to the average American, but they are not so rich that they're completely removed from society or so rich that they have the power to buy politicians/laws to benefit themselves to the detriment of society in general. It's not helpful or fair to group engineers, doctors, and lawyers, etc. with robber barons.

The framing of 99% vs 1% was a poor decision, and they likely picked those figures because they meme well. As you say, though, if everyone was truly taken care of, this would be a moot point.
SUFLI – “click-to-translate” subtitles translator for Netflix (Chrome Extension)
This is a very interesting development!

But doesn't that mean we are merely reimplementing old concepts on a new level? Almost everything we do on VM level we already did on process level:

- Read-only VM images are essentially like statically linked binaries, just better encapsulated when they run.

- Tiny, fast loading VM images are essentially stripped static binaries with dead code elimination.

- Starting those by incoming network request is just like old "inetd" versions started custom handler programs on each request.

- Same with CGI, just on HTTP rather than TCP level.

- Manual maintaining the lifecycle of those VMs like FastCGI in nginx.

- Maintaining the lifecycle of such a started VM is essentially like FastCGI in Apache (or nginx + auto-spawner).

The only real difference is the improved encapsulation (controlled network access and resource consumption) of the running code, isn't it?

What might come next?

- Multiple VMs could share the same images to save memory, essentially reinventing shared libraries and dynamic linking.

- Network traffic into and out of a VM is controlled more tightly, reinventing SELinux. (Perhaps followed by noticing that these profiles are hard to maintain, rediscovering the maintenance issues of SELinux systems.)

- Providing the network traffic shape directly with the image, so these can be maintained at a single place, by the original developers. This would reinvent Pledge.

- Introducing permissions for network traffic, e.g. such that just one group of application VMs can communicate with the database VMs. Ideally with an ACL system as used for managing file permissions. This would reinvent Unix Sockets.
Prior to 2018 at the federal level, this strategy only saves on payroll taxes, which is effectively just the medicare portion: ~2.9% - 3.8% of tax savings.

In 2018 however pass-through income gets to take a very significant 20% deduction off the top. Whatever findings they uncovered in that study are going to accelerate very rapidly under the new tax plan.
Like so many other kinds of national leadership, it occurs to me that the current US administration's restriction, removal and tainting of data (remember the panicked surge of downloads of science data after the election, and the restrictions on what words the CDC can use, and whether "climate change" can be uttered by Interior Department staff) is going to shift the center of "reliable data" outside the US to places like Canada and Europe. Heck, even China can decide to play in that space.

And so the US reduces its voice and influence in yet another area. One example will be that citations of US data will decline; being reminded less and less of US data, researchers and similar will tend not to look for it in the first place.
> The only domain requiring unique productive skills is doctors

Most doctors I know are simply information routers. Unless you're talking about surgeons I don't see what makes medicine more uniquely productive than, say, legal work.
At first glance, Amazon alone employs more than half a million people. Microsoft is over 100k, Apple is about 80k in the US, google's about 60k, and Facebook is around 17k.
There are decades of research studies on this topic in criminology alone that the NYT can tap into. Look up the field of "victimology".

On the other hand, the NYT is not a scientific journal. Supposedly, they know what makes people interested in a topic. They want to start a public conversation, and while that's innocent and beneficial enough, they're starting the conversation on the wrong foot, and commentators like me end up having to talk about what I talked instead.

It would also be interesting if they brought up women-on-men harassment figures, if only to point that the numbers are so much lower, and other data that suggests that this might be indicative of cultural differences between how men and women in the West are raised (and not some innate male proclivity to harass that supposedly has to be socially repressed).
> are valuable nevertheless

... or incredibly harmful.
If having the 10 men and 10 women means inappropriate videos aren't shared at work, maybe it's a net gain because everyone's working and doing their job instead of sharing videos.
https://www.youtube.com/watch?v=uA-TXdE5mpo
I view it differently. If it's not appropriate in the sense that it's harassment for any possible mix of employees (by gender, ethnicities, etc.), it's simply not appropriate period.
Python part is a bit out of date. Otherwise a good read.
> You seem to be more interested in pedantry than in understanding the point of the post, which you've conceded.

Yes, I am interested in responding to what you actually said. Sorry if you can't handle that. I'm going to ignore you from now on.
Furthermore, the correlation with Trump approval is totally fishy. These numbers don't rule out the possibility that men harass women at roughly the same rates regardless, and self-report differently due to their awareness of the issue.
Nice work!

From my classification this seems similar to base16
https://github.com/chriskempson/base16

Is this correct and would you like to clarify the benefits of using themer instead of base16? Have you considered intercompatibility by i.e. allow conversion from and to base16 themes?
There are a LOT of ways to game taxes if you're either an S-Corp or a C-Corp (without going into stuff like overseas, disguising personal expenses as business expenses, and other classics), and the original papeer has a very telling graph showing it (ok, so it's less than a 5% reduction, but it's still a tax break).

See the original PDF, page 72 "The marginal tax rate falls at the top because active S-corporation income is a larger share of total labor income at the top but is not
subject to the 2.9% Medicare tax and 0.9% ACA Additional Medicare Tax. See Section 7 for additional details."

http://faculty.chicagobooth.edu/owen.zidar/research/papers/c...

Not to mention they're going to get WAY bigger under Trump:

http://www.latimes.com/business/hiltzik/la-fi-hiltzik-pass-t...

Edit: as meritt posted, it's going to be like 20% (!!!), not taking into account the other tricks.
Even with Trump's immigration changes, our immigration standards are equally if not more liberal than India and much better than Chinese immigration. Citizens can't even move around China without government approval. Over 13% of the US population is foreign born, not including the over 11 million illegal aliens we have.
Look out, Mofo: new bike-share contender HelloBike nabs $500m
Actually, per a comment above, this article likely understates the prevalence of more serious harassment (bordering on rape, e.g. coercive sex). So this "SJW" doesn't think it's necessarily a good thing.
These data might be impacted by Canada's stance on disclosure:

> Last week the Canadian finance ministers announced that federal, provincial, and territorial governments will require companies to keep information on beneficial owners that can be made available to authorities. In the same week, all 28 EU members agreed to make such information publicly available on registries and to make beneficial owners of trusts available to authorities.

Source: https://www.theglobeandmail.com/opinion/how-much-real-estate...
I don’t and I’m not sure it would be wise to do when it wasn’t anonymous.
Iterative password hashing functions need to be slow to be secure. Their cost factor is borne through consumption of real-time resources such as CPU cycles and memory bandwidth, and therefore cost is roughly synonymous with latency.

BlindHash is a completely different approach. I used data as a cost factor — a massive array of random data, which can grow over time but once a bit becomes part of the pool, it never changes.

Here’s how it works;

First, a fast hash (SHA512) and a secure salt (64 byte CSPRN) turns your password into a random number, call it Hash1. That 64 byte value is sent to a BlindHash Server.

On the BlindHash server Hash1 is used to generate 64 uniformly distributed i.i.d indices into the data pool, which imagine is ~100TB of data, and you read 64 bytes from each location. Accumulate those 64 reads into a 4KB buffer, and hash that. Return that result.

Back on the authentication machine, use the result from BlindHash to HMAC your Hash1 to produce a Hash2. Store/Verify the Hash2 value. Hash1 is never stored.

What this accomplished is basically entangling the password hash with an arbitrarily large pool of data, where an attacker needs to steal >90% of the data pool in order to even start attempting an offline attack.

The bigger you make the data pool, the more data an attacker would have to steal, but the faster the system runs — because more data spread across more SSDs increases read bandwidth since the read pattern is perfectly uniform.

The network carries 64 bytes in and 64 bytes out with each BlindHash request. Size the network pipe to handle your desired authentication load, e.g. 64 * 100,000 = 6.4MB/sec.

Divide the data pool by the available bandwidth, e.g. 100TB / 6.4MB = ~180 days. That’s how long it takes to steal the data pool over the network at full line rate. And the attacker needs virtually all of it to even try to start an offline attack.

For large scale secure password storage, BlindHash provides the means to eliminate the possibility of an offline attack. It’s faster and cheaper than burning expensive CPU cycles, and most importantly security (growing the data pool) and performance (logins/sec) are positively correlated, not negatively. It Scales.

Disclaimer: I’m the inventor, patent holder, and CTO of BlindHash, and I’ve been working on productizing this technology for several years now. As a longtime HN member/contributor I do feel like it’s OK to occasionally pitch my company when relevant topics trend on the front page, as long as there’s an interesting technical component to go along with it!

If you’re responsible for securely storing customer passwords at a large corporation, scrypt/bcrypt/argon2 is not the right approach for you. You’re better off spending those cycles mining Monero.

Let me help you eliminate the possibility of a breach and actually save you money in the process. You can have your own on-prem data pool, or share a massive geo-replicated pool with other large corporations at an even lower cost. </pitch>
Testing Ansible Playbooks with Vagrant
A large number of people here on HN are in the 1% as you only need a household income of $465k. That's easily met by two mid-level engineers at Google, Apple, Facebook, Netflix, AirBNB, et al.
Doctors and Executives are not 'pyramid schemes' in any sense of the word, and profs at elite universities represent a very small economy.

'Management' is a skill, not a 'market manipulation' and a very difficult skill at that.

Most of these 1% work huge numbers of hours, typically had to work pretty hard through school, and are smart and talented people - even if there is shifty stuff here and there, and a lot of 'born in the right family luck'.

I don't know any successful people who are fools who just lucked out through life. They're all pretty amazing.
Side-question: Are they activating the paywall 24 hours after the story gets posted or something?
Ask HN: What are your Security Challenges and Goals for 2018?
I'm a man and it's totally not OK. For me this is a proof of having no basic respect for >50% of people for very shallow reasons. Having jerks at work is a net overhead (regardless how brilliant).
In my experience a good larger architecture is mostly OOP but where the implementations make good use of FP patterns like map and reduce instead of the equivalent loops.
At the bottom of the page it says:

themer is inspired by trevordmiller/nova and chriskempson/base16.

Conceptually, themer is very similar to base16, but:

1. It is lighter, and simpler to use.
2. It is more easily extensible with your own color sets and templates.
3. It integrates better with your dotfiles, especially if you keep them under version control.
I care because landlords are a type of business that can be passed on whole to children and allows for the creation of hereditary wealth and hereditary wealth maintenance without risk.

If the profitability of a business is mostly because of a single person working there who takes most of the profit, when that person dies their children will not be able to easily maintain that income and so are more likely not to be hereditary members of an upper class.
Plummeting temperatures could send world into 'mini ice age' in 2030
I think it's a lot of things. Any lawyer is insured to the level that makes sense for their work, so at some level that's really not a differentiating factor.

A lot of it comes down to things as varied as depth of bench, using their famous letterhead as a club, familiarity and traditional relationship, old boy's network and so on and so forth.

But it's still silly to give a one-conspiracy-fits-all account of the legal world.
It's unfortunate that the most prominent behaviors are characterized so vaguely. It seems that "could be considered offensive by some" is an extremely broad criteria that is likely to be padded with benign behaviors, especially given that these categories are each about 4X the size of the others, and the variance is otherwise quite low. Given that, I wonder what the aggregates look like after throwing these categories out? What percent of men engaged in any of the remaining categories? How are offenders distributed across blue/white collar jobs, etc.?
They acknowledge all of the methodological stuff towards the end. The NYT itself didn't conduct the research and they compared to the results of similar surveys and it was consistent. How desperate are some people to minimise this stuff?
Oh, I do apologise. I didn't realise that you're afraid that saying "I bet SJWs love these articles" will get your life ruined. Sure sounds like you're at serious risk of being victimised. I reckon if your employer knew you'd said that, you'd be fired for sure. "I bet SJWs love these articles." I mean, that's really quite something. The way you hid yourself and said it anyway will really make a difference. It's a shame you have to pretend to be someone else; one day you'll be able to say "I bet SJWs love these articles" without having to hide your face.

Extra bonus; you know I'm being sarcastic, but you also believe it's true and I just don't understand how dangerous it is for you, latter-day Otto Hampel that you are.
Self-reported data is better than no data, as long as the nature of the sample bias is clear (which in this case it is).
I looked at your post, are you referencing the removal of the entire vulnerabilities section on the grounds that it was promoting Tavis?
Well, except all the similar surveys were also self-reported as far as I can tell.

It's worth noting the social desirability bias here. It's likely the problem is actually much worse than the study indicates.
This is really excessively cynical. Any law firm can buy liability insurance, not all law firms have the kind of legal expertise of Cravath, Swaine and Moore or Slaughter and May. They don’t have unique expertise but they have extremely rare, expensive and reliable expertise available in quantity and on demand. When the stakes if a contract goes to court are in the billions you do not skimp on mere millions in legal fees.
> Assuming you are US-American, I shouldn't say that you invaded Iraq either, should I?

I think most Americans are comfortable with the sentence "we invaded Iraq" if that is what you mean. Also "we won our independence from the UK", even if their ancestors were English for generations after that war happened, in the sense that the individual is a member of the group "Americans", and "Americans" is the group that fought the war.