skysight-inc/HackerNews huggingface dataset:
About your first point: Independence. You are less independent of English and more dependent on the binary format and the tools who can handle it. It's a trade-off. And it might be just an opinion, but for me it's not a good trade-off. Learning English was a one-time endeavour for me. But binary formats and tools have to be learned separately.

About what you put in the log message: You can also put different fields in a line of text. Not getting the advantage or trade-off here.

About the internationalisations: As non-English developers we force all our systems who have logging internationalisation to English system language so we have a common ground for the messages. Understanding the English message is nearly no burden. Log Messages are Event triggers, either in code or in a developer's/admin's mind. If I get a log message in my native language I don't know which event that triggers, which makes it actually harder.

Really. I don't know any non-English person who considers log internationalisation a good thing. Fighting anglocentricism is a very anglocentric topic. Outside of UK/US that's a non topic. We (non-English people) are happy that there is a language we can use to talk to each other and we don't really care how it came to be that widely known.

And even if you don't speak English, I don't see the advantage of parsing \x03 instead of "Error:.*". Both are strings that have a meaning which is rather independent of its encoding.
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just step out of 'Machine Learning' bubble for a sec

there have been decades of research into 'Cognitive Architectures' (http://en.wikipedia.org/wiki/Cognitive_architecture) and 'Artificial Consciousness' (http://en.wikipedia.org/wiki/Artificial_consciousness)

there is massive amount of experimental observations on learning and cognition in neuroscience and cognitive sciences (from neurophysiology to psychology) that is largely ignored by Artificial General Intelligence and Machine Learning communities.

On the other hand the progress in Deep Learning, Computer Vision, NLP and Robotics is largely ignored by neuroscientists because these learning models do not respect biological constraints

There is a whole group of narrow domains like Formal Concept Analysis, Statistical Relational Learning, Inductive Logic Programming, Commonsense Reasoning, Probabilistic Graphical Models that don't talk to each other but all deal with cognition and conceptual reasoning using different tools

I think we have a chance to make progress if these fragmented domains converge.
And on Firefox for Android. Blur is very slow, though.
That doesn't sound as impressive as a thin-air holographic projection.
> "give me 10 hours starting from last Friday 2am"

journalctl --since="$(date -d'last friday 2am' '+%F %X')" --until="$(date -d'last friday 2am + 10 hours' '+%F %X')"

Now I'm no systemd apologist but maybe some of the hate towards systemd, journald and pals is unwarranted. If one gives these newer tools a chance, they actually have some nice features. Despite the Internet's opinion, seems like they were not actually created to make Linux users' lives difficult.

If binary logs turn out to be the wrong technological decision, I'm sure we'll figure that out and change over to text logs again. All it would take is a few key savvy users losing their logs to journald corruption and the change in the wider "ecosystem" would be made. But if all goes well... then what's to complain about? :-D
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People have, I think, internalized the logic of arms races. Someone's going to have [scary technology X], so why shouldn't we have it first/best? (Sure, there are answers to that, but none that I think most people would stick to when push comes to shove).
Geekbench Results of AWS, DO, Linode, Vultr and CloudSigma (~2 CPU / 4 GB RAM)
Vote cancellation is weird.

I wonder if posts that have no genuine reason to be downvoted (like yours) get more votes if they add a comment to the effect "Not sure why this comment got a downvote" since multiple people will try and correct the erroneous downvote with no idea whether anyone else already has.

Edit: Ha! Thanks for the downvote.
"The device contains a projector that beams an image up onto a screen, which in turn vibrates up and down at a rapid speed."

http://www.extremetech.com/gaming/174772-voxiebox-a-real-lif...
Good point. The thought actually actually popped into my mind after I wrote the post : "Wall E" and many more films/books have suggested this accelerated learning path.

However this is information only, not interaction, I suspect this will have a serious distorsion effect on how the AI "perceives". It's a wild guess, but I believe interaction is at the root of understanding.

Edit : yes you also mention interaction through video games, which I skipped when I scanned your comment. But then again video games might be still far from the depth of real world interaction, more of a learning enforcer than the source of it - like books are for us....
She actually did it in 2008.
the question about mercurial by "gitdude" is very umm.. leading.
It's not a counter argument to journalctl's usefulness being independent of binary logs, right? In fact using that nice tool for querying I don't really care how it stores logs under the hood.
The system should provide a standard API for writing and reading logs. The precise format of the underlying log files is thus rather unimportant at this level of abstraction. Other than the logging subsystem and recovery tools, there's no need for any software to be accessing such log files directly (outside of the API functions). This is how Windows has done it for years.
Sleight of hand and linguistic gymnastics.

Freedom from inequality comes from freedom to buy and sell goods and labor without* restrictions or borders, inequality is near all time highs because of crony capitalism and corrupt governments.

Edited for clarity
There is no reason for a "computer" to do all that and if it could it would not - all that he talked about is about dealing with the limitations of our brains - our mind the machine would not care because it would not care about its limits - we are as a computer one big limited system constrained by the process that brought us into being - chance and natural selection. An ai is not constrained by this anymore than a dog is constrained from finding the same thing funny. humor is not a problem for us because we are part of the problem - we are a constantly derived huge word puzzle. an AI would not be that - AI would have a purpose.
I noticed the ambiguity and clicked on the link just to figure out which was intended.
it has nothing to do with being "net positive" to those around you. You can be the best thing that has happened in people's lives. call it low self esteem, self worth, whatever, its just that for some reason, no matter how positive you are to them, you always feel like a burden.
I don't know about Google, but I believe Facebook keeps all of its code in one gigantic Mercurial repository.
"Let's just rewrite all the crypto ourselves! In assembly!"

Sorry to be a buzzkill, but that sounds like a recipe for disaster.
yes, works
True, we still don't know how "learning" works in brains. But it works in our neuronal network. What about combining some real neuronal cells with technology?

I remember one documentary in Discovery Channel, where some scientists make use of rat brain cells cultured on a circuit to build a small robot, which learns to avoid obstacles on it's path.

A similar video is here -https://www.youtube.com/watch?v=1-0eZytv6Qk.
> back-to-the-basics take on what "is" computing... to build your CS (of whatever brand you like) atop

I feel that we've given many years of attention to functional programming, and it's been disappointingly unfruitful in most areas of CS, such as computational complexity, cryptography, machine learning, or computer graphics. Most new ideas coming out of the FP camp are applicable only to FP itself, like monads. We've discussed that before: https://news.ycombinator.com/item?id=8563817

Part of the mismatch is that many interesting algorithms are impure and cannot be easily made pure. I'd like the "foundation" of CS to give a faithful mathematical description of what computers can and cannot do. Is that too much to ask?

But the bigger problem is that FP treats functions as black boxes, and that's just not enough to prove interesting results in most areas of CS. A better "foundation" would try to describe computational behavior and reason about it, instead of abstracting it away. I admit that's a very vague idea, but I'm not smart enough to make it concrete :-)
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It is odd. When there's a strange downvote people might then make more upvotes because they can see it was downvoted, but can't see when it's been corrected, because the scores are no longer visible. But voting is weird anyway. I don't take it personally, and I don't want to complain, but I genuinely get confused when there are downvotes I don't understand, and I want explanations purely so I can decide either that I was right and to hell with it, or I was wrong and I need to reconsider things.

With just a downvote I don't get the chance to learn.

Still, there we are.
If it's tested extensively, it should be fine. Somebody has to write the crypto.
I've never used mercurial outside of TortoiseHg. In fact, the only time I've used mercurial is when I was attempting to build Firefox from source before I realized that they do a git mirror thing so you don't have to touch mercurial at all.

I don't know much about mercurial. I use git because somebody said it is easier to rewrite history in git.
This is probably the kind of trough that's meant: http://en.wikipedia.org/wiki/Watering_trough, detailed image: http://en.wikipedia.org/wiki/Watering_trough#/media/File:Cat....

If you "think away" the actual trough and keep only the liquid, you get the cuboid that the text is referring to.
During the Korean war Douglas MacArthur lobbied to use tactical nukes on the Chinese forces over the border.
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OpenSSL no longer really qualifies as "adequate safety".
Of course, you'd probably do a little better than that, because at no point would your car be carrying all of that gas. But the trough would have to get wider when you went uphill or had to get going at a light.
Not persuaded.
Not to disagree with you in any way, but `jq` is something you might look to add to your toolbox. As must JSON as we see anymore, it's a good tool to have.
Yeah, the point of moving from C to Go would be to get away from all the disasters. But if the core is small enough using short bursts of inline assembly to actually calculate the cipher, while all the complex protocol handling and buffer manipulation is done in the safe layer, it would be a good solution.

Edit: that does indeed appear to be what they've done. In particular using the AESENC instruction.
https://github.com/cloudflare/go/blob/master/src/crypto/aes/...
curl 'http://api.openweathermap.org/data/2.5/weather?q=london&mode... &>/dev/null | jgrep -s main.temp | figlet

Put this in a function. Done.

Gist here since copying and pasting above didn't work. https://gist.github.com/zaargy/384889cb44960e8559d5
There's the explicit gag itself, and it's an old one, of stepping on a scale.

The real joke, however, is in fact that it is the president. It's more humorous because it shows the president as a real person. It's unexpected, and out of context of how we typically understand the holder of the office of the president of the united states should behave.

That's the main joke. So yes, the finer details are important. It's not just a funny picture.
without formal methods it's impossible to fully test crypto implementations, such as ECDH, because the number of possible inputs are enormous. bugs in small proportion of inputs can lead to fault attacks. and furthermore side channel attacks are very common.
Really, really have to say I disagree with (iii). Purity is growing more and more day by day. From other comments you seem to have taken a fairly non-standard definition of purity and I'd encourage you to stick with the normal one as it'll let you talk about more interesting things—see further comment on (viii).

I don't think (iv) is open at all. The fact that you can encode everything as function passing is an interesting trick, but it's merely one of several (you can, e.g., also encode everything categorically or via supercombinators and graph reduction, which turns out to be more practical for lazy languages). Function application is just one really well understood semantic foundation.

I find (v) far more subtle than you make it out to be. The standard static/dynamic types divide is silly because both sides are talking about different things. The static side wins completely because honestly, taken at face value, they don't claim that much. All languages are typed, some have interesting type theories, some compilers reject programs which are syntactically OK but violate the type theory.

(viii) is interesting. In my mind, you've conflated this with what most people would call purity---however, monads are merely an implementation of effect typing/purity. Others exist and are experimented with. Also, composition of monads always works as desired... there's no strange edge-case to it. It's merely that they don't compose like functions in a simple way. When you examine what they would entail you learn that they ought not to as well.

(ix) HKTs are sort of a gateway drug to type-level computation. It's remarkable how many languages just more or less let their type-level language wither and die. I'm not claiming that HKTs are a slam dunk victory, but I would be willing to bet that the evolution of languages will lead us to (a) having them universally in the next two decades and (b) wondering why everyone was so hung up on HKTs---I mean, I suppose I can understand singletons, but HKTs? Really?
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Herceptin. Trastuzumab inhibits the effects of overexpression of HER2. If the breast cancer doesn't overexpress HER2, trastuzumab will have no beneficial effect (and may cause harm).

he original studies of trastuzumab showed that it improved overall survival in late-stage (metastatic) breast cancer from 20.3 to 25.1 months.[1] In early stage breast cancer, it reduces the risk of cancer returning after surgery by an absolute risk of 9.5%, and the risk of death by an absolute risk of 3% however increases serious heart problems by an absolute risk of 2.1% which may resolve if treatment is stopped.[2]
ARM is now the competition that keeps things interesting in the x86 CPU market.
I didn't mean you can't be productive in functional languages.
What I'm criticizing are the platforms and I don't see that as too much of a subjective matter.

For me as a user Haskell(the platform) is inferior to, say, Go, simply because I can manage external packages that much easier. Thus if I needed to get something done I'd rather use Go, not because I think it's a better language than Haskell, but because of the pain in dealing with package versions, building, etc.

Basically what I'm saying is that you don't see that much adoption, and thus data to endorse the productivity claims because of the platforms and not because the languages per se are bad.

Pg said people don't use lisp because it looked weird and it's not popular[0] and I think it applies to functional languages in general.
I don't think you can/should solve the former, but by having friendlier/better platforms you could start solving the latter.

http://www.paulgraham.com/iflisp.html[0]
They were doing exactly the same thing as him (and worse) but they killed him.
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What are the most effective marketing channels to get subscribers to this video

http://tinyurl.com/ngj4n2n
To be fair, the author is evaluating a computer based on a task our brains have specifically evolved to be good at, facial recognition, social interaction, and familiar settings. You could turn it around and find tasks that computers are good at. e.g. Watch a month's worth of highway videos and count how many cars passed.
Isn't it all a gamble in the end?
Why Email Marketing May Not Be a Good Strategy for Some Businesses
All the low-level crypto is written in assembly. And not only for speed, but for ensuring properties like constant-time execution, etc. It's the same for OpenSSL, and the same for commercial crypto libraries. Go is not at all different here.

The difference is that the higher-level crypto is written in Go, not in C; Go is memory safe, much more strongly-typed in general, and with run-time bounds checking which eliminate buffer overflows.

The bugs are almost never in the low-level algorithms, they are in the higher-level components.
The irony of a click bait article being posted by a new account. Deliberate?

But it was good. And I was a new account once too.
Why lack of information is killing cops
I know where you're coming from but I think this advice ignores the truth of such positions: that they are prestigious/well-paying/otherwise attractive enough to cause candidates to invest time and money into pursuing them.

For example, why does Google sometimes take close to a year to make a decision on a candidate? Because they can afford to, with a pipeline of thousands of qualified candidates enough of whom will be OK playing along with Google's timeline in exchange for the significant CV boost, higher salary, prestige, experience, etc. The same applies to university applications - a lot of people will spend fortunes in time and money to try and get into Harvard, Stanford or MIT because the upside of having these schools on the CV is so high. Both prestigious jobs and universities (whether or not they should) do open doors, allow you to raise more funding and faster, to get higher positions all things being equal, to get your CV read in a pile of 200...

So it comes down to valuing each position's Net Present Value (NPV) and the probability of it being a success, and deciding whether this is the most attractive use of your time and money. Let's say AirBNB has an NPV of (an additional) $3 million over the next 10 years thanks to the network and career boost, and you have a 5% change of getting it, the value of taking the interview is still $150k. Assuming you weigh negatives 9x as high as positives (can't remember where I read about this cognitive bias), if the interview has a total cost (including opportunity cost) of under $16k it is worth doing. Of course, at 5% chance of success per position, it's probably worth applying to more than just AirBNB.
Arithmetic savants and trained arithmeticians can come a lot closer to the calculator, showing that the usual human brain layout and/or architecture is a really poor fit for performing this type of calculations.

There's also some evidence that the "efficiency" of the more powerful parts of animal brains (including humans) simply comes from a sort of n-dimensional conditional railroading, which would work like this if my understanding is correct: if you map (B/W) visual inputs to XY axes of a slice of neurons, then when a line is formed, this fires up a line of neurons, which allows a direct connection between the Z±1 neurons of the first and last neurons on the mapped line, so this connection becomes the line. These Z±1 neurons have pathways to various other nearby other potential Z±1 neurons; a connection lighting up between Z±1 neurons that don't have a straightline connection over the XY map could detect different shapes. Then the Z±1 layers and their connections could be creating highway maps between both Z±2 neurons and diagonally-offset neurons that don't "fit in the grid" we're imagining here (remember, we're in 3D and neurons don't form a homogeneous grid, so this is all abstraction anyway).

These second-level connections, arguably identifying something like shapes, have connections in such a way that the next level up detects something else, etc. (insert magic we don't understand), until the detection results in recognizing a specific object, while the side-channel connections we haven't mentioned yet but kept occurring at every level connect to a different side-channel ZY map for, say, the position of the object (with its own layers of processing that eventually connect to the object concept neuron so that the "position" is associated with the recognized object), and/or perhaps other side-channel maps or parallel XY mappings for various other things. And of course, a lot of these things connect to completely different parts that we ignore here, and a lot of the information indirectly makes its way to the conscious mind in this way; the brain doesn't compile a complete vision report and submit it to the conscious mind in one download, it's all using the same hardware.
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Temperature accurate to three decimals? That's kinda silly. It would be more useful to display the "felt temperature".
Do you have any reason to believe that to be the case?

Yes, but only within the limited circumstances of the cold war.

I strongly believe that nuclear war between two equal and opposing parties is effectively impossible. The game theorist Thomas Schelling wrote about it - each party can only 'win' by demonstrating they're more willing to risk all out destruction but, importantly, never actually go through with it otherwise they lose. With nuclear war both sides lose completely if they go through with it, but they can lose less by giving up. Consequently one side will always, eventually, capitulate before a nuclear war happens because that's actually better for them.
Maybe I am misunderstanding but it sounds like you are encountering bad json log file practices because json entries are spanning multiple lines. Which implies they are being printed in non compact form aka prettified. Thats a problem in the pure text world too. And hurts worse when it happens there. Its kind of an apples to oranges comparison.

Json log files should ideally print using compact form (which will never have raw newlines) so each entry only takes one line, which is then separated by a raw \n

If that practice is followed each line will represent the complete json object. So you can then pipe the file through jq, Perl, python etc one line at a time.

Printing prettified json to a log should be avoided because it then requires having to reconstitute individual events syntactically before being able to grep for an event. if pretty output is desired pipe it through a prettifier.

Config files are a different story, those should most definitely be pretty printed with one atom per line for nice diffability and the best read and editability json can offer. Sadly json for config files is, unfortunately, a bad idea if you want humans to enjoy editing them by hand. In that case using yml is the best option I have encountered (ansible).
So while we're at it, here's a shameless plug for my own spatial network analysis tool with a python API. It produces weighted network stats (accessibility, flows, severance, efficiency) which typically feed into spatial data analysis.
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Why doesn’t Google know where I should vote?
5 Must Have Apps to Boost Team Productivity
I agree with your guess that Watson covers 6/7. From the clinical geneticists I've talked to, variants of unknown significance (where a person differences from the reference, the impact of the difference) are investigated manually through literature searches- often just basic text matches on the variant name.

Regarding paper parsing: there are companies that employ hundreds of PhDs that read papers all day long and enter the data into a database based on ontology (Ingenuity). IBM would license that database and use it as a prior.
It looks alright. I suggest you look into minicrm's work since they expand very well. What kind of customer interviews have you done in these 2 years?