skysight-inc/HackerNews huggingface dataset:
According [indirectly] to one of the comments, the issue is that there is no solution which solves all the problems in the context.

Reference:

https://gcc.gnu.org/ml/gcc/2003-08/msg01257.html

Specifically:

There are two things missing. The abililty to turn on the workaround in c (i.e. emit FP rounding instruction after every operation), and a bug fix for the register spills.

Even with those things, I think we are still in trouble. In the first case, having explicit rounding instructions eliminates the excess precision problem, but it introduces a double-rounding problem. So we have lost again there. This is probably not fixable without changing the hardware. In the second case, fixing the problem with reload spills eliminates one source of unpredictable rounding, however, we still have the problem that local variables get rounded if they are allocated to the stack and not rounded if they are allocated to an FP reg-stack register. Thus we still have the problem that we get different results at different optimization levels. So we still lose there again also. This might be fixable by promoting all stack locals to long double to avoid unexpected rounding, but that will probably cause other problems in turn. It will break all programs that expect assignments doubles will round to double for instance. If we don't promote stack locals, then we need explicit rounding for them, and then we have double-rounding again.

I really see no way to fix this problem other than by fixing the hardware. The hardware has to have explicit float and double operations.
I wonder if storing the hashing parameters next to the hash is the right approach to take for systems. Your system isn't going to support all hashes (adds a lot of library bloat, you don't want to support weak hashes), so you'll probably want one specific algorithm/parameter set, with room for upgrades in case weaknesses get discovered (not likely to occur often). A single byte/varint, starting at 0 and incrementing for every new parameter set sounds reasonable. A downside would be interoperability, but if that's your main concern then perhaps a human-readable string representation of the hash algorithm/parameters would be preferable.

What are the benefits of using Multihash?
The VR technology is honestly very good right now, if we are talking about the actual hardware.

What we don't have yet is content. We need 1 company to put out a triple A game, and it will hit mainstream.
May I ask why you want to run pg inside kubernetes? I'm trying to wrap my head around why that's a thing that people want to do.
Paraphrasing:

"Computers are different from all the rest of science. That's why there's so few women in the field."

How are computers different from the rest of science?

"They just are!"

That's not an argument.

"You're a dishonest jerk!"

I think I understand where you're coming from now.
Obviously a throwaway.

I worked at a Series C startup in the Bay Area as an architect. I made about 450K in total cash comp + lots of options.

Some of the executives were clearing over 500K a year in cash.
you have to drag this table around in all code that uses the protocol and remember to update it all the time

Won't some kind of table always be necessary unless the type contains actual bytecode implementing the hash algorithm?
Not to sound like an asshole, but there probably is. There probably are roles paying $500k a year doing exactly that. Not many, but they will be out there for certain people.
I'm at $95k Canadian. These threads make me feel bad.
Author here. I showed an example - short lived http 1.0 connections. I haven't done benchmarks but my hunch is that you can run accept at in low tens of thousands times per second from one CPU. If you have more than, say, 10k qps the accept() might well be the bottleneck. You can imagine having a box with 64 CPU's, doing short-lived connections, and being limited by accept() done on only one CPU since it doesn't scale.

Second issue is cache locality. If you do accept() in one thread only, then you will need to move the new accept-ed client socket to another worker thread. Depending on details this might not be efficient - aRFS comes into mind. (but frankly, epoll alone won't help here, you need SO_REUSEPORT with SO_INCOMING_CPU).

Even if you don't agree that scaling out accept is a real concern - that's missing the point. The point is: the epoll() model should take this into account and at least support this problem. Or loudly say that scaling out accept() with epoll is not possible. But neither things happened. Up till kernel 4.5 it was impossible to do it correctly, but undocumented, from 4.5 you can use the EPOLLEXCLUSIVE flag, which I feel is a hack.
I remember that in university we had a test on a toy 16-bit floating point ALU. We had to walk through each of the steps in the ALU for the usual operations, showing the bit patterns at each step and keeping track of precision loss, etc. Because we had to track state and some aspects of the test were randomized, there were a few cases where identical operations on identical inputs resulted in different outputs due to the residual state.

During the next lecture, someone sticks their hand up and says, "this FPU thing is so nondeterministic, who in their right mind would use floating point for 99% of the kinds of work that we use computers for?"

The professor says, "you should think real hard about that the next time you decide to use a floating point type in your program."
I'm curious if you can really design a practical API that avoid all the issues the author talk about.

Even on something as simple as interrupt delivery to a single consumer, you MUST be prepared to handle merged and spurious interrupts -- I would argue that any driver that is not prepared to do so (in the general case) is buggy.

Maybe it's easier to do perfectly with an epoll/kqueue API for some reasons, but, without having tried to think much about it, I can't imagine why it should be. I have the intuition this is way harder. Actually I'm not even sure if I can have any intuition about the difficulty to achieve the behavior wanted by the author of that article, because the author did not actually specified the behavior he desires...
I think that's just a bad substitute for the real question: What's the big-O notation, how do algorithms differ based on the CPU / memory usage and existing data format. Nobody uses merge/quick sort as originally defined anyway. In reality it's going to be some mix of algorithms with a threshold.

So why not ask what you really mean by either asking the theory (big-O), or real world practice (you're adding a number to a large ordered data structure - how would you do that, what's the chosen structure, tradeoffs)
Didn't Linus said that all he cared about is getting code back, with no concern over patent grants such as the one in gplv3? Head-shaking and muttering is all good but the kernel developers has had a long time to take an active stance against software patents and has consistently chosen not to do so. As a project they have chosen not to get political about patents, so this is the reality they have embraced.
Codes reserved for app-specific things should satisfy your concerns. coming soon: https://github.com/multiformats/multicodec/issues/39

One thing you should consider about using full names (like "sha2-256") is that you still have to keep a table. What does "sha2-256" even mean? you know from context. you know that maps to a particular algorithm and particular set of implementations from context.

Writing a table and distributing is cheaper than writing a new implementation of a new hash function and distributing. The "distributing code" part still has to happen.

I think what you would like is if some body (NIST + all others who make hash functions) was maintaining the registry. That's fine, we can give this table onto IANA (though that's harder to update than a PR on Github).
Exactly. It's Afghanistan with the Soviets, all over again... the blowback is going to be ugly and protracted.
Currently making ~$300k/year in total comp.

31 years old. 5 years of experience as a hardware engineer, and 2 years as a software engineer (back-end).

Master's degree from Stanford.

Practice hackerrank, cracking-the-coding-interview, read a programming/architecture book every few months, till you can ace programming interviews and understand your field really well.

Living in NYC, where the financial companies have driven comp levels really high for software-engineers.

Working at a big-4 software company.

Currently at my 4th company. Interview and negotiate aggressively at many different places every time you switch, so you can get 20-40% increases.

Don't know how much this helped me, but do a side-project and blog about your experiences.
graduated in 2009, found a sales job on craigslist at a startup, startup was invested in by Google, worked in another startup, got recruited by facebook, gg
Wouldn't 'git grep --line-number ^TODO' fix that (only match TODO at the start of a line)? Maybe with some whitespace matching if you indent your TODOs?
I don't think Sweden is on the radar screen of most Americans, regardless of political perspective. The only popular reference to it that I can recall is when Trump mad a snide remark about unrest in Sweden, the left-wing press mocking him for doing so, then the right-wing press doing the happy dance when there were some riots there that supported (or could be spun to support) their narrative.

I'm fairly politically engaged, and my largely uninformed opinion of Sweden - and all of Scandinavia, honestly - is that it's a largely homogenous society with a relatively long history of stable governance. There don't seem to be a lot of analogues to American society there, so I haven't cared to learn more about it.
Samsung Launches the 9.7-inch Galaxy Tab S3: Snapdragon 820 with 6000mAh and HDR
If you like the shooting in AS, join us in Rec Room playing paintball. Its simple enough mechanics and free so it has the largest community with people always playing.
I didn't claim that Linus came up with the design from scratch, nor that git was less experimental than monotone in 2005. Just that no one used monotone, so git was not a reduction in safety/assurance compared to any in-use SCM. And as mentioned, it's goal was speed, not cryptographic assurance.

I also was surprised that git became so popular, I thought mercurial would win for "ease of use". But I've never been an advocate or influencer of popularity. I think that's mostly due to GitHub, which got it to a market-share tipping point.
No. Focusing on competence AKA merit makes your company more competent. Focusing on something else necessarily hinders your ability to focus on competence.
+1 to this. Rez Infinite was close to the best few hours I have ever spent with a computer. That said, most of my coworkers didn't seem to get the same thing out of it that I did.
Yours is not an isolated experience. The games I've played which felt like full VR games were Superhot, Asseto Corsa, Chronos, and Elite Dangerous. Hopefully one day you'll be able to connect a PSVR to a PC or those games are ported to PS4 because each and every one was fantastic. God knows, it'd be great to get Rez and Psychonauts on PC.
Their testimony can be used to build a case against Assad in any future international tribunal.
> I fear that if there were valid criticism to be heard, it would at best only fall on deaf ears.

I'm not closed to this point of view, but it sure seems to be a rare case indeed.

If you look at it from the reverse perspective, climate scientists have been explaining /basic/ material and conclusions to deniers for decades now. If you want to criticize, I don't think there should be a peer-review barrier but you sure should at least be familiar with the body of work you're criticizing. Or else, how could you possibly contribute anything of substance? Go read the IPCC reports, or /something/. That's just common sense. A lot of criticism fails to meet that minimum bar, and also has usually been addressed beforehand.

I'm not a climate scientist, but right now I'm taking a graduate level class in databases and data systems. We're reading a lot of papers, some from academia and some from industry. But what I'm realizing is how lacking in nuance and content the discussions on even highly technical places like HN can be at times. Like when I see stuff like "NoSQL is bad for joins", it's like "really? on what system? under what conditions?". The ease with which laymen can assert conclusive-sounding statements on a whim is terrifying. The more you learn, the more you get the opposite instinct - to withhold judgement until something seems very clear. This destroys conversation dynamics when scientists are pitted against climate deniers. And a lot of times, I suspect that the arguments made fall in the "not even wrong" category. Then, the people who make the assertions aren't even willing to listen to the counterargument because it's "too technical". As if everything has a pithy one-liner response. In the end, this results in a massive amount of frustration on the part of the scientists, which leads us to the pickle we're in today.

Anyway, this discussion reminds me of the whole discussion in the 50s/60s about the health effects of smoking, and how it took forever for doctors and scientists to convince people that this was real. All the tobacco industry had to do was to criticize specific bits and pieces, discredit specific researchers, call things "inconclusive", and suddenly their criticism was as legitimate as a huge body of research. That's the dangerous bit here. Take a look: http://www.who.int/tobacco/media/en/TobaccoExplained.pdf
From the order form, you can get a personally signed copy for $150 (or $49 unsigned). Pretty sweet.
Why do you classify genius as scummy?
Because it's difficult to identify aspects of computer technology that are unique to the field and not present in other fields in which women have far better representation. It's simply difficult to come up with a simple explanation for why women would be just fine with graduate-level math, molecular biology, astronomy, or statistics work, but not with computers --- especially given the fact that computer work dominates most of those fields, too.

And the explanation would need to be simple, because it competes with another explanation, which is that computer technology is systemically biased against women, the way every other profession was before those professions took explicit steps to correct disparity.
Remember the Waldorf-Astoria before it closes Wednesday
making 220k base salary, as an architect in bay area - about 20 yrs in the industry, 5 here in bay area - java/hadoop etc etc
Only place I've seen them used has been to annotate the notes of a deep learning course at Stanford. http://cs231n.github.io/
A Leader’s Framework for Decision Making (2007)
Sean Spicer targets own staff in leak crackdown
Yes. There is nothing about floats that should make them unusable in a set.

In particular though, it's fairly common to use std::sets (or std::maps which use the same underlying data structure) to maintain something in a sorted order.

I ran into this myself when implementing A*. I was using an std::map with the float as key for the priority queue. Under GCC with default compile arguments it would randomly hang or crash due to GCC breaking the set invariant.
Yeah I've seen positions offering 200k base salary for less then 10 years experience with java.
The demos can be so compelling sometimes that they make me believe in VR as a product. The content needs to catch up however. I think when Fallout 4 VR is released is when VR will begin to be worth the cost of entry.
Also have this. Perfect size on this phone, and waterproof. Looks almost new after two years.
These kind of coding questions aren't about the interviewee's "problem solving" skills. It's purely a question of basic competence in the field. If it's general problem solving capability you're after, then you're right, there are much better ways to do that. In the case where a job interview involves multiple one-on-one interviews, it might make sense to have one interviewer focus on basic competence, and another interviewer to focus more on more general problem solving skills.

You might think we ought to be able to assume a basic level of competence, but lots of people in the industry think you can't. And to the extent that you can, that's often because the person sitting in front of you in an interview had to get through an initial online screen where they had to do some sort of coding exercise.
While I agree in general that PRs are better than forks, I don't think what you're saying is totally fair. Your choice of licensing explicitely allows forks (and almost anything else) to happen. There have been many discussions on the topic [1], and there is no easy solution.

Then, your choice of words is not ideal:

>NOTE: I no longer actively maintain this package. I'd love to get PRs to keep it going though!

If it's not maintained anymore then I as a developer don't really gain anything (bugfixes, features) by submitting a PR vs. just forking myself. So the choice to fork is understandable, even if it's not what you intended to happen.

[1] https://arstechnica.com/information-technology/2014/10/how-d...
VR definitely needs to be developed for intentionally. Not least because the performance requirements are significantly higher.

However VR isn't really restricted to a first person view, you definitely need to respect motion sickness and avoid it as much as possible but there are plenty of good games that use a third person viewpoint on the action. What you really shouldn't do is take control of the camera and when you do (e.g. for locomotion) avoid styles that cause nausea.
The PhD will only be useful in a small (but growing) subset of data science jobs. Their are data scientists who develop new algorithms and techniques, and those who apply the. For application, the PhD is probably overkill and extensive experience with a bachelor's, or a master's is better. For theory the PhD can't be beat, of course. I say the opportunity costs are high, and should be carefully weighed, because I have my bachelor's and am making more than a data scientist friend of mine who has his PhD. The vast majority of what he learned in the PhD program he hasn't found useful in the real world (yet, anyways). So it's all about what problems you want to work on. Personally I thrive in the application arena of data science, while others thrive in the R&D data science arena. If you like one you probably won't like the other.
I want to hire people that can write robust, maintainable software. Unfortunately, I do not know how to test for that. At my company we do not do algorithm quizzes because, for better or for worse, algorithm mastery is not really important for most of our work. We mainly talk about work experience in the interview.
Genius is a non-scummy site, turned itself around ages ago.
I think it's hard to figure out on whose side to intervene. It's also unclear if the western world should start a military conflict with Russia.
How is that any different from a short sale investment?
I make $190k base:

$190k base + $10k signing bonus + RSUs = ~$300k total comp

> what your role/salary/experience is.

Senior full-stack engineer. Located in SF.

> How did you get your high salary?

Interviewed at many companies and received multiple offers. Kept every door open, made sure the company/team knew I was excited to join, and moved the negotiations and base salary forward. It helped a lot to have an existing open offer when companies asked what I was making previously. This anchored their starting offer.

> How have you been raising it?

Switched jobs my salary increased by $10k, $40k, $10k, and $60k. Contracting for 4 years increased my yearly income to $330k. The biggest raise was interviewing at 10+ companies and choosing the best offer. Got a lot of rejection emails too.

> Do you plan for it, or does the company reward you automatically?

I never received a substantial raise without switching companies. Larger companies with lucrative bonus programs might be different.

> Do you switch jobs a lot?

First company I stayed 5 years, second 3 years, third 1.5 years, fourth 6 months, fifth just started a few months ago.

Out of my friend circle I'm not the highest paid engineer. A friend just accepted a senior engineer position a recent IPO company making $210k base. Another friend is an eng. manager at a finance company making $1m but not sure if that's base or total comp.
Great. A 100-line python or perl (or even bash) script instead requires the whole machinery of node.js to work. Brave new world.
How did that turn out?
Take a look at http://learnmicroservices.io
That has links to numerous resources including some introductory articles.
This summarizes real world data science really well, in my experience.
Sleaze merchant is jealous of more successful sleaze merchants, warns of sky falling due to people not playing by the set of rules he understands.
Amnesty International works tirelessly to document human rights abuses in all of the other conflicts you mention and has done for many years. What exactly is your point?
Properly implemented floats will never fail that (barring NaN). That gcc sometimes does is a compiler bug, not a float problem.
I've been following the Syrian Civil War for the last 5 years. The null hypothesis: every faction has done horrible things. That's what happens in war. It would be an exceptional civil war indeed if the central government (or any other faction of significance) did not commit atrocities. I understand not wanting one's country to be involved in the war. I don't want my country to intervene in the SCW either. I don't understand the resistance to recognizing the horrible things done in Syria (by the central government or otherwise).

Is the idea that if the Syrian government commits atrocities then Western powers have to intervene in the war? So to prevent a probably-disastrous intervention people need to deny that the Syrian government commits atrocities? I don't think that is a logical chain of reasoning, if that is indeed what is going on. There are all sorts of horrors in the world where additional intervention by outside powers is likely to be worse than inaction. It doesn't mean that we should pretend that the horrors don't exist.
On a related note, testing floating point equality should be known as a recipe for unexpected results.
I was a PhD student in mathematical logic, and I know a couple people who got PhDs in this area and became data scientists. One thing about this field (and other areas of math) is that almost everyone in it feels mediocre. It's like 10% of the people are 10x better than the other 90%, 1% are 10x better than the next 9%, .1% are 10x better than the next .9%, etc. The top two people in the field seem to be notably better than everyone else. Another thing is that the problems are incredibly arcane. They have no connection to practical concerns or even often other parts of math, and also you can't really explain what you are working on to someone who works in a different area of mathematical logic (unless maybe the person is extremely good). So you have a lot of people getting PhDs who are very, very smart by any normal measure but who would be doing mediocre and arcane work in mathematical logic. Part of the appeal of working in data science or working for the NSA or something is that it is somewhat down-to-earth and people will think you are really smart even if you are at the bottom of the top .01%. (And you can do really great work at this level -- I don't mean to say it is all about caring what other people think.) It is a little weird that the blog post is so negative in a way.