skysight-inc/HackerNews huggingface dataset:
I don't think it's obvious at all, and I think people often mistake a number of other things in others (philosophical agreement, expertise in a domain, certain social skills, among others) for general intelligence.

There's also considerable evidence, IIRC, that, while the upper limit a person can reach in intelligence is genetic, that environmental factors play significant roles in both how closely that limit will ever be approached and how well/long what is achieved will be maintained.
I have exactly the same approach to interviews and hiring as you, it's never failed me yet. I don't care if they can code fizzbuzz in 20 languages, I want to know if they are ready to carry on learning when they need to and they can find information they don't currently have.
Not exactly. Given enough time and a lot of hard disk, you can put the entire 1.9B triples into any database -- that doesn't prove that it scales. Also, if the database uses a single global mutex lock for all reads and writes, again it's not a scalable architecture.

Scaling is about throughput and latency. This post is trying to determine whether adding more machine power actually lets the db perform better.
These are the reasons I'm interested in C++ reflection. I am maintaining a library called Ponder on Github with this in mind. http://billyquith.github.io/ponder/

I'm not interested in exposing everything in an executable. I see that as unnecessary. I just want the relevant objects exposed in a useful way.
Whoever down-voted the comment above doesn't probably know that "democratization of management and movements of money" is really one goal of this company. ( http://fortune.com/2015/05/21/paypal-ceo-dan-schulman/ )

Now it's seafile.de, a couple of months ago they started to block accounts used to pay VPN services. What's next?

I am not judging the company, because I am sure that they would like to have users to pay everything possible via their services. That's fine. I just find it incoherent to claim that they are democratizing the way to manage/move money around.
Half-Life 3 on VR would be the killer app. It would be this generations Lotus 1 2 3.

Though I personally feel VR for video games are a lot like Wii its awesome for a while then its collecting dust throughout the world. I really think the future is Augmented Reality and VR will be for mostly media consumption.
OP is PR for Imagination Technologies.
10 Super Awesome Tools for Android Developers
> It targets similar compression rates at higher compression and decompression speed compared to deflate using zlib

I don't doubt this is true, but I'd expect a little benchmark on the README as a proof. It would be interesting to see how LZFSE compares to LZ4 (https://cyan4973.github.io/lz4/).
Yes and it is normal. It is very hard sometimes and you need to push through that. I abandoned lot of projects in the past because of this: now I push on and usually things work put actually as long as you persist.
India Says It Has a Mobile Forensics Tool That Can  Handle Iphone Encryption
> As a result I have numerous half baked personal projects.

Every decent developer has dozens of half-baked personal projects. Some get finished, some don't. All eventually get abandoned.

They are never a waste.

If you go through your codebase, you will find that you re-use code and techniques that you learned on your next project. This is how we learn.
That's a pretty huge WTF request.

Can you sue Paypal for basically telling you "break the law or don't use us" (I think that's a pretty bad idea on ideological grounds but I wonder if it's technically possible)? Especially since Paypal has to be regulated within the EU in some way I'd say such a request should result in at least a cursory check if the EU license (iirc. they operate as a bank) of Paypal should be revoked/suspended/investigated.
This is a common pattern for bugs and exploits, it seems. X is safe, Y is safe, X+Y is exploitable.
Oh, so I guess the Sunway thing isn't as much like Neo conceptually as it looked to me from what little information I had. (I wasn't thinking about the ISA.) Of course the media are mainly useful for indications to chase primary sources.

The point about the OS related to the Linux-based one for Sunway, but maybe it only runs on the management processor anyhow, with just offload to the others. I'd commented in that respect that we really don't want something like Linux in an ideal world, so I'm pleased to see mention of L4.

Thanks for the comments, and good luck.
Not the entire point. Relational databases have schemas that are not well suited to graph structures, and SQL is also a barrier. A better question is whether you need to implement your own storage backend or whether something like Postgres would suffice.
I am not sure, but if my cofounder and I get kicked out after 3 months, then we have saved 3 months of rent money. Both of our families are loving and entrepreneurial, so I do not foresee this being too much of a problem, but it is always good to keep in mind that our families may not get used to our return.
Simple Go HTTP Service Auto-Discovery and RPC with Sleuth and ØMQ
Now that it is "morning", I'm not sure that I can do justice to this question here...

But certainly we have to take back the term "computer science" and try to give it real meaning as to what might constitute an actual science here. As Herb Simon pointed out, it's a "science of the artificial", meaning that it is a study of what can be made and what has been made.

Science tries to understand phenomena by making models and assessing their powers. Nature provides phenomena, but so do engineers e.g. by making a bridge in any way they can. Like most things in early engineering, bridge-lore was put in "cookbooks of practice". After science got invented, scientist-engineers could use existing bridges as phenomena to be studied, and now develop models/theories of bridges. This got very powerful rather recently (the Tacoma Narrows bridge went down just a few months after I was born!).

When the first Turing Award winner -- Al Perlis -- was asked in the 60s "What is Computer Science?", he said "It is the science of processes!". He meant all processes including those on computers, but also in Biology, society, etc.

His idea was that computing formed a wonderful facility for making better models of pretty much everything, especially dynamic things (which everything actually is), and that it was also the kind of thing that could really be understood much better by using it to make models of itself.

Today, we could still take this as a starting place for "getting 'Computer Science' back from where it was banished".

In any case, this point of view is very different from engineering. A fun thing in any "science of the artificial" is that you have to make artifacts for both phenomena and models.

(And just to confuse things here, note how much engineering practice is really required to make a good theory in a science!)
The commercial surveillance complex is just a special case of the military industrial complex. No conspiracy is necessary to explain the greed in traditional defense contracting; surveillance tech is just the latest variation.

Also, the current obsession with machine learning is amplifying the problem. It's easy to misuse data analysis (e.g. overfitting the model until it says what you want it to say). Data is seen as valuable on it's own even if it isn't useful "now". This produces an effect similar to tulip-mania where everybody wants as much data as possible even if it isn't currently useful.

Finally, add in bad incentives where failure is rewarded with more contracts. As Mudge (Peiter Zatko) gave a very good description[1] of this problem which he called "game theory is a bitch". The solution is to make retaining data toxic with liability.

[1] https://www.youtube.com/watch?v=h9wXq6oRBnI#t=1173
> KiloCore processors ... store data and instructions inside i) local memory, ii) an arbitrary number of nearby processors, iii) on-chip independent memory modules, or iv) off-chip memory.

Ah, like GreenArrays' GA144, which contains 144 discrete cores - each with a small amount of memory - that can communicate with each other. The rationale with this chip is that you store data in the memory of one or more neighboring core(s) if it won't fit in the ~64 bytes (IIRC) of the core you're working in.
If AMD can come through with the RX480 and works with VR for around $199 USD. That makes VR a lot more accessible.
Every site has a hivemind of sorts, but HN really hates it being pointed out. I still roll my eyes at every source list that begins with [0].
The reason it's slow is because python interprets it's input. It essentially introduces major indirection for instructions to be executed.

So for '1 + 1', you can't just output some fast x86 instruction and inline it. You'll usually need to jump to where the python vm will do 'a + b' in C. You're having to do a bunch of redundant work at a higher level to emulate the CPU (sorta).

That's why you have JIT compilers that will read '1 + 1' and compile the appropriate machine code, store that in an executable memory region and jump to it. First time might be slow, but after that it's pretty fast. Because you need to jump to the dynamically generated code, you usually compile whole functions at a time.

This topic is super complicated but also super interested but I tried to simplify it a bit here.
This is not possible. The torrent protocol works by checking the hash of each file that it downloads so it can reseed the file. If these files were changed by even 1 bit then they couldn't be reseeded back into the torrent network.
What we can learn from an Indonesian ethnicity that recognizes five genders
There's also seven years of OSX before the iPhone happened.
How to Prevent a Heroku Dyno from Idling
Without commenting on Haskell, et al., I think it's important to start with "good models of processes" and let these interact with the best we can do with regard to languages and hardware in the light of these good models.

I don't think the "stuckness" in languages is other than like other kinds of human "stuckness" that come from being so close that it's hard to think of any other kinds of things.
Their product was only of use to a bigger company.

Just like the slew of CV startups getting bought by Snapchat.
The writes for Dgraph actually happen in O(log N) time where N = number of subjects for a given predicate; and a background job then syncs the posting lists to disk later. So, that performance wouldn't be any worse than what we observe here.

However, to do writes like you would do them in production would require you to sync a mutation log to disk, before applying it in memory and returning an OK. This particular operation bounded by disk I/O would then become the bottleneck, and not help with doing benchmarking for the database. Which is why we didn't make writes part of this particular benchmark.

Dgraph does concurrent writes very well. To determine that, you can run Dgraph batch loader. It can load up the entire 21M triples from the blog post, in 20mins on an n1-standard GCE instance.
https://github.com/dgraph-io/dgraph#loader-performance

When jumping from 2 to 5 nodes, we did want to ensure that the nodes have to communicate to run the queries, as they would in a real-world scenario; which is why the performance wouldn't just double.

I think you're putting a lot of emphasis on the size of the data. While that is surely important, the size itself isn't the only thing which proves scalability. It's about the concurrency, throughput and latency -- and determining that they do improve when you add more hardware power to the cluster.
"No."
> I assume that the reason why most of these failing tests are failing is not a regression in core functionality of Make but rather because of new features were added to GNU Make since 2006.

There were a number of bugs in the 3.81 release that I assume they now have tests for, since 4.x has been rock solid. (Off the top of my head, if you made a certain shape in the dependency graph with .PHONY targets, then .DELETE_ON_ERROR stopped working)
It's very difficult to believe the part about "energy efficiency". If it were true then someone can just burn the nanotubes later to produce electricity as proposed in the previous comment.

The new extended electricity plant that produces nanotubes and burn them have the same maximal theoretical electricity output than a traditional electricity plant, but if the "energy efficiency" were true then the new method would produce more electricity.

The traditional method is something like burning the hell of the methane, use the heat to produce electricity and release all the CO2 to the atmosphere

The new method would be, bun the hell of the methane, use the heat to produce electricity, use the CO2 to produce LiCO3, use part of the electricity to produce nanotubes and LiO, burn the nanotubes and use this additional heat to produce electricity and release the CO2 to the atmosphere. The calculations are more complicated because the fumes have different temperatures, and other technical details.

But for me it's unbelievable that an indirect method that transform the CO2 to nanotubes and burns them ads "energy efficiency". I'd guess a 30% energy lost in each step.
> Scaling is about throughput and latency.

under reasonable constraint. throughput and latency from a cacheable dataset is moot for big data.
The root problem with the SaaS project example is that you should be aware that, in general, many people are involved in projects like this. If you want to push it alone it is obvious that the number of tasks will be much bigger than when you are an employee. This kind of projects require a different approach and if possible one or more collaborators.
I call BS on that.

It is true that banks will go a long way to try to satisfy banking regulators. But unless you have some evidence I am simply unwilling to believe that banking regulators can make up any restrictions they like without regard for the actual requirements of federal law.
The clearest evidence yet that he's not the real creator of bitcoin.
There were some standard,
old techniques I didn't see.

For the set of real numbers
R, a positive integer n, and
a function f: R^n --> R, we
seek x in R^n to minimize
f(x). Let z in R^n denote
the value of x that
minimizes f(x).

Borrowing from D. Knuth's
mathematical typesetting
system TeX, we let x_i
denote component i of x.
More generally we use the
underscore to denote
subscript.

Assume that function f is
differentiable and let
D_x f(x) be the derivative,
that is, the gradient,
that is, the vector
where component i is the
partial derivative if f
with respect to component
i of x.

(1) Line search. Suppose
we have iterations
j = 1, 2, ... where x^j is
our jth estimate of z.

Then, for positive real number
s, our step size, we can
the usual gradient descent
is

x^{j + 1} = x^j - s D_x f(x^j)

Well, with this approach, it
need not be that

f(x^{j + 1}) < f(x^j)

So, an improvement is,
for each iteration j, to
do a line search to find
the set size s. If f is
convex, then there is a
simple, standard approach
to how to adjust s on this
like search.

(2) Conjugate Gradients.
Gradient descent is
vulnerable to a lot of
movement in directions
that are nearly orthogonal
to the best direction.
The classic technique
conjugate gradients
after n iterations
improves this situation.

(3) Newton Iteration.
The simple Newton iteration
for, say, square root
generalizes to
a function of n variables but, of course,
requires finding second
derivatives of f.

(4) Quasi-Newton.
Look up quasi-Newton that
estimates the second
derivatives of Newton
iteration from the
gradients from the
iterations.
The author already changed the link (as mentioned below). On that note that---with some GNU projects use GitHub as a mirror---GitHub fails GNU's ethical repository criteria for hosts:

https://www.gnu.org/software/repo-criteria.html
What does "from Mars" mean here?
I hire plenty of data scientists - if I had to give a single piece of advice: gain a deep understanding of the techniques you're using.

it's not sufficient to say "oh, we used a support vector machine", and when prompted for more detail about how it works to shrug and say you just copied and pasted code from the internet and tweaked parameters until it worked.
Google to Offer Better Medical Advice When Searching for Symptoms
“But he does good work.”
Margins and addressable userbase. For many people, their mobile device is their only device. And if they do own a laptop or desktop, they're likely to keep it longer than their mobile device since it's likely to be fast enough and subsequent version aren't likely to provide huge advancements that affect most users.
It shares similar traits, yes. You can interrogate something to find out what API it provides for you. The transport here is XML (SOAP?) and the binding is written in C. However, we are discussing reflection in C++, which is more generic than this. A C++ reflection library would not have one specific purpose like this.
I think Paypal has very strong brand recognition with the average consumer for such an esoteric product (online payment processor as opposed to say candy bar). Anecdotally many people enjoy how easy it is to pay with Paypal and that they have a perceived extra layer of protection. This is doubly true for this case since credit cards are historically not as wide spread in Germany as elsewhere (and thus Paypal linked to your bank account becomes a pretty attractive option). Most "Paypal is bad" stories I'm reading are at the expense of merchants not buyers. As long as they control buyer mindshare it's hard for merchants to opt out imo.

I wonder if there's studies or analysis on this (expected revenue loss with no Paypal option). Were I to start an online shop I'd prefer something like Stripe but would be pretty worried about missing out on a lot of revenue.
I think this is massively overestimating our ability to suspend reality.
Thinking you can go faster than light for communication is the same as believing perpetual motion or even being a flat earther.

You can't do it, there are no hacks to do it. It's a law of the universe. No matter how many SciFi movies tell you other wise.

I just don't get the acceptance of this anti-scientific concept.
Tutorial: Luigi for Scientific Workflows
bfgs -- Broyden, Fletcher, Goldfarb, Shanno update for
quasi-Newton?
I think the locomotion issues will be the end of this round of VR. Teleporting around the virtual space is not immersive by any means. Direct movement (e.g. with a joystick) with current head mounted displays automatically results in motion sickness for the majority of users. No solution in sight, as far as I know.
Naive question: Are our ad-blocked web sessions killing the small guys?

My morning routine starts with:

• loopisight.com

• daringfireball.com

• marco.org

• verynicewebsite.net

• inessential.com

and with some exceptions, posts these days are just links to podcasts (which I don't have a desire to listen to). I've been told that it is because podcasts are an actual source of income, whereas blog posts are not so much a way of earning a living.

Makes me wonder if it is that podcasts are more lucrative, or that blog posts are no longer lucrative.

Edit: And did ad-blocked loss of advertising play a role in MacNN's demise?
Our families are a fairly entrepreneurial bunch, so they are supportive of this. Our parents are first-generation immigrants from cultures where it is not unusual for adult children to continue living with their parents.

I definitely appreciate your perspective. It is important for my cofounder and I to have a very balanced relationship with our families to make sure that they benefit from the arrangement and that we do not incur stress.
Facebook shareholders vote to issue Class C shares to keep Zuckerberg in control
I'm sure they could be doing better, but I notice that Amazon has a region in Frankfurt specifically to address German data protection concerns.

There are Amazon employees who could be ordered by the US of A to break German law and extract data from customers at the Frankfurt site. In my judgment, the chance of their being prosecuted in Germany would be indistinguishable from 100%, so the real question is, has Amazon set up its organization such that people who are safely in the US can access such data.
OK then what type of graph would be hard to store in RDBMS?
There are obviously queries that one would want to run on graph data that RDBMS will not run efficiently (but the queries in this test are actually trivial for RDBMS). In what way is SQL a barrier compared to learning query language used by some graph database that is not applicable to anything else you do?
"A better question is whether you need to implement your own storage backend or whether something like Postgres would suffice". You could just use a more established Graph Database that actually performs well on complex graphs?
How to Use Asana for Project Management: The Complete Guide
Curious about results so far.
I wonder what you think so far.

In particular, I liked the tuple-calculus they define; it can be extended to support just about any permission I can think of (although it does require reversing DNS names, which is slightly ugly).

I have a scheme to release a v2.0 of the standard someday in my copious free time.
One VM to Rule Them All, One VM to Bind Them (a 3-hour Truffle/Graal tutorial)
How to evaluate a machine learning model in R, part 2
Peter Thiel-backed banking startup Number26 raises $40M
ecryptfs shouldn't be running kernel_read() from the page fault handler anyway - it should pass the read off to a work queue and put the process to sleep until it completes.
It is not unlikely that you will never get to the same league as 'the inventors'.

Most people are mediocre at everything they do and will always be. Most likely that includes you. We live in a culture that doesn't just tell everyone that they can easily outgrow mediocrity, no, this culture tells people they are above it from the very start.

The following advice doesn't apply to geniuses or those who can be, but it applies to the majority who will read this:

The best you can do is look back on your life and see if there is only mediocrity. If there is, you have to be honest with yourself and recognize if it's so because of factors that you can still change, or not. For most people reading this the latter will be the case, which means you simply have to live with it and stop trying to influence the world, because everything you end up doing is going to make things worse (for you, and everyone else).
If you're using split-diff I also recommend MiniMap [0] and the Minimap-Split-Diff plugin [1]

[0] https://atom.io/packages/minimap

[1] https://atom.io/packages/minimap-split-diff
Until you have at least one but probably both of these people identified and "recruited" it sounds like your dead in the water to me. Unless, you have someone that's willing to give you money to find and recruit the missing pieces. I'm not trying to be negative just suggesting what you need to focus on.
This is exactly right given our current understanding of the universe. FTL travel violates causality, which is a fundamental principle of the universe.

I wouldn't go quite so far as to say it's totally impossible though. There is a whole lot about the universe we don't understand and I can't rule out the possibility that there are entire branches of mathematics and physics that we don't know about.
Good point, it gets tough remembering all the little differences between the two.
Intel launches Knights Landing Phi and other goodies
Same link posted a few days ago.

https://news.ycombinator.com/item?id=11922484

Previous (but brief) discussion.

https://news.ycombinator.com/item?id=9689471
Indeed. Thank you for pointing this out.
Catalyst137 Unveiled as World’s Largest Hardware Technology Hub
Video shows China bank employees being spanked
Show HN: Blooming Structures
Anonymity Doesn't Always Promote Online Aggression