skysight-inc/HackerNews huggingface dataset:
Many of the design elements from the DH.88 can also be found in the DH.98 Mosquito,[1] probably the most successful multi-role aeroplane of WWII.

[1] https://en.wikipedia.org/wiki/De_Havilland_Mosquito
William Orbit.

Completely prolific and varied but the standard is just so high

Try his entire catalogue.

Here are just a couple of highlights:

Who Owns the Octopus? - https://m.youtube.com/watch?v=AX8lmn1tk4c

Water from a Vine Leaf - https://open.spotify.com/track/00z9Rax2KTHqKLKYnGHzNk

Brand New Bong - https://m.youtube.com/watch?v=ELrdoimfed0

Montok Point - https://m.youtube.com/watch?v=XIPhxU0vZh0
This article is critiquing the unstructured get-to-know you interview. It is not critiquing highly structured interviews with clear goals, nor technical challenges, nor references checks or past performance.

In your example, how would you structure a series of questions and procedures to limit the risk of marrying someone who will abandon you or cheat on you? I think you can apply good interview process techniques to this quite well!

1. Have they been divorced or cheated on someone before? People who have been divorced before are much more likely to divorce again. The 50% divorce rate in the US is slightly misleading, as many of the divorces are concentrated in repeat divorcees. In fact, among younger (early to mid twenties) first-time marriages, the divorce rate plummets to something like 15-20%.

2. Have their parents been divorced or cheated? Children of divorced parents are much more likely to get divorced themselves.

3. Have they been physically, emotionally, or sexually abused as a child? People with traumatic early childhood experiences are much more likely to develop trust issues with long-term partners, especially if they never had extensive counseling.

4. Do they have a good relationship with their family? People who have a difficult or unstable relationship with multiple family members are more likely to see tumultuous relationships as a norm.

This is all equivalent to reference checks in a job.

Then a long dating / engagement period is necessary. How do you they treat you during this period? Do they cheat? Are they abusive? Do they leave you during a period of difficulty? Do you have the same religious views? Do you split housework evenly? Do you both want kids? How do you view money? The three most common reasons for a fight among couples are 1) money, 2) housework, 3) free time (and how to spend it).

People who are otherwise happy and well-adjusted adults who get married and then divorce bitterly after 10 years are not the norm. Most divorces can be predicted. And most divorces happen before 2 years of marriage. If you are aware of the warning signs and are not blinded by a "gut instinct" I think you can definitely minimize the potential for marrying a snake -in-the-grass.
Can it replace the jQuery dependency in Twitter Bootstrap?
You would probably need to use a software renderer for that, I imagine.
Java is pretty darned graspable, at least I think it's way closer to Go than C++. What do you think are the biggest things that make it hard? The language? Warts like int/Integer? Library size or organization? (This is a real question, I can't look at this stuff with "fresh eyes.")
It is daunting for sure. I stewed myself in the ecosystem last year by writing a couple open source libraries and fell in love with it. Java was the sexy language of the 90's, ironic because The best way I can describe it is the exact opposite of the current sexy language, JavaScript.

Java is great, the best, when I'm trying to build something creative. It's like having access to an entire parts warehouse vs a toolshed for most other languages. Unlike especially JS, most libraries are well tested and most people agree on doing things a certain way. There's not a lot of unknowns, almost no flux, and once you know the rules you can focus on your problem and ignore the "ecosystem" almost entirely.

The complexity can be looked at from a different perspective, I see it as similar to Roman characters vs Chinese. Learning 26 characters is a hell of a lot easier but with a couple thousand you can say the same things with a lot less writing. Once you've gotten over the cognitive hill of learning the complexity it doesn't really get in the way. It's there when you need it, and you ignore it when you don't.

Contrast this to JavaScript where most advancements redefine workflows or parts of the language core libraries. It feels like the most exciting thing about JavaScript is how unstable it is, something that scares the hell out of me after working on 15+ year old code. What you trade off with complexity in Java is definitely less work than keeping up with js for more than a year.

This sort of became a js/Java comparison because there's a ton of similarity in the hype between them and their lifecycle so far. Java was not always so complex after all. You can see the complexity of the JS ecosystem and language growing steadily and I have no doubt that in five years it will be just as complex as Java. The complexity is driven by the big guys that actually need it, and being the big guys, they also have the most influence on what the language eventually becomes.

So to recap, no, for the vast majority of projects the complexity is definitely not justified. It's there so the language can support the 1% of projects that need all that. On the other hand, once you know your way around it's fairly easy to ignore those parts. What access to all this stuff really gives you is power. As a footnote, give JS some time and it will be the same. Any language picked up by corporate interests is basically destined for overengineering.
There's a reference in the article that covers that kind of scenario.

The additional 50 students that the school interviewed but
initially rejected, did just as well as their other
classmates in terms of attrition, academic performance,
clinical performance, and honors earned.
That has to be one of the most employee-hostile hiring strategies I've ever read.
The more I scroll, the stupider I feel. Ugh.
Yeah packtpub is a real crapshoot. They're great in that they'll seemingly publish whatever tech subject you want to write about. The downside is they publish anything...
I've bursts. Sometimes I can work three days non stop and sometimes I strugle to write any good code. Luckily I've some margin to decide on what to work every day so I do documentation or unit/integration testing the days my brain is downclocked.
You rarely maximize windows on large screens, so you need to move the mouse much further to reach the menubar.

I actually prefer the dock on the left-- I keep it there on MacOS also. That's preference too but it makes sense as most displays are widescreen with much more horizontal than vertical space available.
It's not just diabetes - exposure to pesticides increases risk of suicide, lymphoma, ALS. congenital anomalies and reduces fertility. There is a solid case in choosing organic foods. See summary of risks here http://outcomereference.com/causes/77
I guess that's reassuring.

But I wonder how much salt is mined. Only one sample was plastic-free. But maybe it's mostly commingled. If one were really interested, one could look at plastic content vs Cl-36 (nuclear fallout) level.
Sure, they do quality in general. I'm just saying it's a bit surprising for a non-tech company to outperform long-established tech companies in a tech field, and I think that tech schedules vs. furniture schedules may explain that.
Lots of coffee shops have fireplaces. The rest is covered by free WiFi. Not the end of the world as we know it. Well, actually it is, but not because of coffee or prostitutes.
The AsicBoost inventors also wrote a good technical explanation at

https://arxiv.org/pdf/1604.00575v1
tldr: The Dow 30 index is a bit absurd, however it's not as bad as it seems because of portfolio theory.

The Dow 30 correlates highly with the S&P500 index over medium-long periods of times (approx more than a month) [1]. This correlation is due to the fact that the 30 stocks that are selected are arbitrary but not random. They are selected by a human process which considers which companies contribute an important factor to the overall market [2]. Of course this process will be imperfect because it's vague, however it gets pretty close.

Don't forget, according to findings from portfolio theory, it's possible to replicate an index with only a small subset of the components of that index [3]. There's a whole field of work describing how to do this [search google for 'replicating index'],

In fact, replicating an index with a small number of stocks is exactly how 'smart trading' companies like wealthfront and bettermint make money. They find multiple non-overlapping subsets of the S&P500 which correlate strongly with S&P500 performance. Then they buy subset A, and if a loss is incurred in any month, they sell subset A and buy subset B. Since A and B are highly correlated with each other (ideally r>.99) and with the S&P500, the investor should expect the same return in the future, however can book a capital loss which creates a tax refund. Shifting from subset A to subset B avoids a wash-sale allowing the capital loss to be recognized [4].

The Dow 30 is certainly not an optimal index, however it's a case study in showing how selecting the "top" companies for some reasonable definition of "top" will earn a return approx. equal to the market (represented by S&P500) no matter the strategy (in this case price-weighting instead of mkt cap weighting can be considered a strategy).

The reason it's cited so widely is that there's a lot of historical data on the Dow 30, whereas every other index is less reported.

[1] Yahoo Finance comparison of Dow 30 vs. S&P500 chart http://finance.yahoo.com/chart/%5EDJI#eyJjb21wYXJpc29ucyI6Il...

[2] Dow 30 index is built and maintained by a subsidiary of News Corp. https://en.wikipedia.org/wiki/S%26P_Dow_Jones_Indices.

[3] http://www.etf.com/etf-education-center/21038-how-to-run-an-...

[4] http://www.investopedia.com/terms/w/washsalerule.asp
I wouldn't be surprised if there were sources for each of these happening on some occasion at a 17th-century coffee house. I would be quite surprised if they all happened, with regularity, at the same coffee house.
> Lists of facts

This has me mulling whether that might be a better approach to administering law-school exams than the traditional analyze-this-hypothetical-fact-situation approach. (I'm a part-time law professor.)

More generally: I wonder to what extent school examinations can draw useful lessons from job interviews.
OS/2 was nothing but an unimportant distraction to my teenager self. :D

The only software I've got nostalgia towards, is anything related to gaming as I grew up: C64, Amiga then PC finally took over until this very day.
I think you have much better chance long term and you can probably scale up if you want to do so. With the anchor client you are stuck in a very comfortable place but you can't raise rates, you can't do different things or hire people.
Both Java EE and Spring provide a huge amount of functionality and do it in an uniform way, so you don't have to glue lots of different libraries together. They aim for enterprise world, where this functionality is required. Not every project need it, so sometimes it might be not necessary. IoC is awesome on huge projects, but if your project is 10-20 classes, it's just unnecessary abstraction. Distributed transactions increase robustness, when you're working with multiple databases and message queues, but if you're creating website with a single database, you just don't need it. WebServices implementation is a must, when you have to integrate with someone, who's exposing their API via webservice and you'll drown in details, if you'll try to implement it manually, but if you're using lightweight REST APIs, it's quite possible to do it without any frameworks.

So it's good when you need it, and it's unnecessary over-engineering for simple projects.
> No wonder headhunters have such a good business. Not that they're more discriminating, but they can pretend to be the solution to an intractable problem.

Do companies view them this way though? I've always thought that hiring external recruiters to bring in a bunch of candidates is done to outsource the scummy task of bothering people via phone, linkedin etc.
A concrete problem that the author misses is the need for a better understanding of SPMD semantics. GLSL has the notion of "dynamically uniform" values, i.e. values that are the same across all shader threads that arise from one draw call, but this notion isn't really properly defined anywhere. It involves an unholy mixture of data flow and control flow that doesn't seem to appear anywhere else in PL theory.

Stuff kind of just works because GLSL doesn't have unstructured control-flow (i.e., there's no goto), and people have a mental model of what the hardware actually does and use that for the semantics.

But a proper study of those semantics, and how to carry it over to unstructured control-flow, or to what extent it is possible, would be awesome.
web-components development with data binding with slim.js
http://slimjs.com New library for quick and fun development of native web components, no black magic involved.
You are arguing that by performing the algorithms for perception, one is conscious. I am arguing that algorithms alone aren't enough, and that yes conscious is still some unexplained physics that takes the results of those perception algorithms in our brains and generates our awareness and experience from them.

I am not trying to win any argument, but it does annoy me when people argue with incomplete information and try to trivialize consciousness, because of what you know about some basic neural nets in computer science. Look at this video released last month, where scientists show a model for just 3 neurons [1], which they think is super important to consciousness. Only 3 neurons out of billions. There is just so much we still don't know.

[1] https://www.youtube.com/watch?v=5s5I-rUyDTA
Real Engineering has a nice explainer on this topic:

https://youtu.be/7rXGRPMD-GQ
Is there any good starting point to use lisp in the same way as I would use go? I mean I write web servers and command line tools in go. As an editor I use vim.

Some time ago I used DrScheme (now Racket) to write Scheme but I never found it to fit easily into my workflow/use-cases.

So I would I like to use the language with the following workflow (100% terminal):

- write code with vim: vim main.lisp
- simply compile the code to binary: lisp build main.lisp
- execute the compiled program: ./main

Any ideas?
Shaders are SIMT (single instruction multiple threads).
Was in the students union for my faculty. We pulled out all stops to make things as efficient and cheap as possible(we actually sold them below cost because we found other ways to subsidise them). 10ish euro maximum performance semester for all the textbooks that were used in the classes, and printing thesis was 50 % of the next cheapest option... if we had doubled our prices.

We also did "university politics", basically creating pressure for professors to make good textbooks. I typeset one myself for a professor who wanted to "beat" another one.

Join your students union, union or local cooperatives and cooperative oriented parties people. Infrastructure and necessities should be run like that or by government institutions.
I think it's kind of the whole point. The instance of the application exists to service one request and then goes away. How many instances there are scales with the number of requests.

And if you have an unpredictable workload, that may be the most cost effective and responsive solution.
If you ask someone to predict a coin toss, and use the methods we use today for interviews, you'll end up with a 50/50 chance at best. Yet some people guess the coin toss correctly. It must be some unmeasured "gut" that's doing a good job for those people, right?
Show HN: A new interactive crowdsourcing social map
> The WRT54G is also 15 years old. That's probably longer than the lifespan of a smart lighting system.

This is probably true, but also depressing. Dumb lighting systems have a very long lifespan, essentially as long as the wiring survives, which is mostly until a remodel or a catastrophic failure; but a smart lighting system is only expected to last 10 years at which time we have to rebuild the system at great expense with whatever is new and hip and trendy (not to mention, the ten year old system was already greatly expensive).
In my experience as a Google engineer, this is mostly false. None of the work I or any of the people I know well at Google is on petabyte datasets; most people just aren't on the hot path of indexing/websearch/youtube. In fact almost none of the stuff I was asked about in my interview has been relevant to my work. I have thought about complex algorithms two or three times in the past year.
I wonder if we can extrapolate to marriages and to how arranged marriages (at least in India) having a higher success rate. Usually the parents on either side decide on a match based on family background, financial stability, education background etc,. rather than letting the to-be married decide.
Syntax: A Generative Introduction, 3rd edition by Andrew Carnie. I got it used, so it's probably a bit more expensive if you want a new copy, but it's a great book.
The ocaml one is very annoying because the bytecode interpreter reliably evaluates arguments left-to-right but when you compile to native code it reliably evaluates right-to-left (or the other way around, I don't remember).
If you hold the actual bonds you can choose between having a predetermined cash flow or selling the bond early to make a capital gain or loss.

If you buy into a bond fund, it is a different story because they typically are going to buy and sell bonds to maintain a constant maturity distribution. A lot more people buy bond funds rather than bonds since bonds come in rather large denominations.
Are you listening, Mr. Thiel?
That's extremely well said. While it certainly beats the alternative of rolling something like it yourself, I've struggled a bit trying to get in the flow of tf, pardon the expression.

My impression is that it's an ecosystem that's developing incredibly rapidly with all the associated growing pains. Even for such a simple-on-the-surface task as feeding very large datasets into the graphs, there are many different ways, some deprecated already, some about to be deprecated by functionality not in 1.0, etc.

It's also quite new, but the distributed execution, while awesome, still requires a huge amount of hand coding and tuning the machinery, reminding me quite a lot of just rolling the damn thing in MPI yourself. I'm very excited to see where distributed tf will be in a year or two, but it's a chore today.

I'm really bullish on their Cloud ML product, a tool to auto-distribute the execution graphs and associated data ingestion, but the documentation and examples for that are a bit all over the place at the moment, and require writing models to conform to the newish Experiment API, which is also a bit underdocumented and underexampled.

My frustration is likely only because of how awesome tensorflow actually is. It's new, but so promising that I want to use it for everything, regardless of the development roadmap!
> When I say "Alexa, what's the weather today?" I'm coding.

Having worked (albeit briefly) on similar systems in the past, no, really, you aren't.
They removed it from his iTunes account, not his local iTunes library.

Since it is a sale, I stand by my position that it is on the buyer to keep purchased files safe, and being able to redownload files from your iTunes account is a curtesy service that Apple offers, but you cannot expect them to guarantee it.
A Billion Wicked Thoughts
Totally got it, thanks, Luke! I would love to read that. =)
This discussion misses an important element, the skill of the interviewer. It is unsurprising that unskilled interviewers' assessments are poor predictors of future performance. It would be interesting to measure the accuracy of interviewers who have had years of experience interviewing, hiring, and managing people.

Here's how I think it works. Skilled interviewers are biased toward rejecting candidates based on any negative impression. Structured interviewing has the same effect. It's the precision versus recall tradeoff. For this use case only precision matters. Extremely low recall is fine.

Also, in the GPA prediction example, the interviewer is penalized for predicting a low GPA for a person who performed well. But in hiring, there is no penalty for failing to hire someone who would have performed adequately.

(Yes, I understand there is an implicit assumption in my argument that candidates are not in short supply, but that's usually true, certainly at Google)
This is the real reason. The 757 could cruise at Mach 0.8, but it's a lot less efficient at that speed.

The 757 use to make the SFO-JFK route in a little under 5 hours, these days most flights make it in just under 6 (a 20% increase in time to save fuel).

Air travel is technically capable of big improvements, but economics don't work out.
There was a pixel-accurate test suite for OpenGL 1,0 from Kronos,[1] but it predates programmable shaders. It tests the geometry and texture processing. It's not free.

[1] https://www.khronos.org/opengl/adopters/
Yup, I'm certain there would be a setting to change for the former and a solution for the latter. I was unlikely to sink time into customising it though given that I had nothing invested in learning it and the switch was easy.
Software that can turn horses into zebras (from UC Berkeley)
Uh... yeah, that's kind of a silly question.

React was created by Facebook for use at Facebook, and shared with the community. The React team builds React openly, invites contributions from the community, and deliberately shares work on the project with the community, but they also have to work with Facebook's product teams to meet Facebook's internal needs.

There's a great writeup of React's history at https://facebook.github.io/react/blog/2016/09/28/our-first-5... .
Smarking (YC W15) Is Hiring Sr Customer Success and Many Others in SF
I disagree fairly strongly. Maybe this is reasonable for lower level courses, but in students' third or fourth year of study it seems short-sighted to expect the bulk of their learning to happen in live face-to-face lectures. Requiring them to learn independently, be it from prerecorded lectures or textbooks, allows classes to cover a lot more ground and (importantly) save lecturer face-time for the task it's actually best suited for: reacting to students' individual needs.

On covering more ground: this isn't just about expecting students to spend "their own time" learning things not covered in class, it's also about more efficiently using their time. With textbooks (and, to a lesser extent, prerecorded lectures) students can learn at their own pace. They can spend more time on the parts that they find difficult without holding up the rest of the class, and they can move more quickly through the material that they understand easily.
That question has also been asked so many times most candidates who have done a few minutes of googling can give you the "right" answer. See here: https://github.com/alex/what-happens-when/blob/master/README...

I'd probably start here to lighten up the mood due to how cliche the question has become:

https://github.com/alex/what-happens-when/issues/231
Linux NULL pointer dereference due to incorrect	proto_ops initializations
> would probably become the #1 database server
> if administration tasks like SHOW DATABASES weren't
> accomplished through \l

If you type \?, then psql lists all of the commands, and it's not hard at all to remember the ones you use the most. For the ones you use less often, there's \?.

For the programmer who chafes at such terse command-line syntax, I imagine that they're the type of developer who wouldn't use psql at all, but instead one of the many graphical tools that list databases and so forth on start-up for you.