jzila

This talk is way too long and not very information dense. I jumped through it a little and liked what I saw, but I was wondering if anyone had a link to a white paper or an overview that could summarize the language features.

Typically the perpetrators in these cases will trickle the data out over a very long period of time, thus evading many alarm triggers.

Looks like this is a blog post providing a demo and accessible description of the research in this paper (linked in the post): https://research.microsoft.com/pubs/211297/onward14.pdf.

The previous HN discussion on this topic is here: https://news.ycombinator.com/item?id=7702796

Responded here: https://news.ycombinator.com/item?id=8201486

I investigated Tableau. It seemed to be expensive and too Windows centric: Tableau Server and Desktop both require Windows (which we didn't want), and we couldn't use Tableau Cloud because we didn't want to expose our data outside our DMZ.

This is one of the first solutions I've seen to the data analysis problem that I'd consider a real solution: the ease of use of spreadsheets but with the question answering power of a database.

As one of my tasks at my previous job I investigated a bunch of data analysis/reporting solutions for our use. None of them provided that combination with any finesse. We ended up writing our own solution as a thin wrapper over SQL that output data either to the browser or to Excel. It served our purposes, but it was a compromise.

This new feature from Chartio, if the video and post are to be believed, would have been perfect. Now if only they offered an appliance so companies could use it without shipping data out.

There's a documentary about the project here: http://vimeo.com/92381391. Fascinating watch.

From the article, "Suppose that r and g are both fixed quantities which do not change over time." This is a straw man that I didn't get in the book. The idea I understood from Piketty is that whenever g is greater than r, _no matter how different_, inequality grows. Since you can have g > r, with g approaching r with time (g = r at infinity), capital simply continually takes up a larger piece of the economic pie.

Prior to now, many of the approaches I'd seen targeted women specifically. The tactics listed in this article instead focus on trying to abstract out what could make a good developer _in the future_.

This is elegant to me because it approaches the problem in a bottom up way: "how can we more equitably target candidates so that we don't miss potentially great fits?", instead of top down: "how can we include more of these specific groups in our candidate pool?"

Author Hugh Howey (http://www.hughhowey.com/) wrote one of the most successful self-published Kindle series to date (Wool, and its sequels Shift and Dust).

He (along with an unnamed co-author) wrote a report that analyzed data from public sources about authors' revenue segmented on publishing model and popularity, among other dimensions. The results are fascinating.

Yes, Seattle-based Shippable, which announced over $2M in funding yesterday. https://www.shippable.com/ http://techcrunch.com/2013/12/10/techstars-seattle-startup-s...

If it's anything like the 2013 Nexus 7, it'll be a micro SIM.

Did you enter the pieces/recordings manually or does it automatically analyze the piece and score?

Either way, it would be cool to see a writeup about how you implemented this.

Nice! Works for me now. Great job :)

Still seems to be down, but with a different error message.

They don't need to have that full money, however. They pay another company a typical interest rate between 3 and 5% to post that bond on their behalf. So you probably need less than $1M per year to fund those bonds.

The bigger issue is that it takes lots of time and effort for back-and-forth with each state to get authorized. One person has maybe the bandwidth to obtain compliance with up to 3 states at a time, and this is for someone who knows the legal background very well. So you need to staff a pretty large compliance department off the bat to become compliant before engaging in money transmission (and thus before earning revenue). That's hugely expensive.

source: I work for a money transmitter.

Is there a blog post associated with this decision somewhere? Is my scenario of logging in with a Google account that uncommon?

(just FYI, until this decision, HN had the most seamless signup procedure I've ever encountered on a website)

The problem is that California redefined the definition of "physical presence" to include affiliates. So not only would Amazon have to charge taxes on behalf of affiliates, but just by having affiliates in California they'd have to charge taxes for any California purchases. That's what they cannot abide.

I suppose the tie-in is simply that we hackers think differently from scientists. It's much easier for us to visualize a complex tree of logic than for people who are not accustomed to it. The second purpose of the anecdote was to illustrate that there is a complete lack of software testing knowledge within the scientific community, or even the recognition of the need for it. All of the "testing" they do is on production data. There is no unit testing anywhere.

My girlfriend is a PhD student in a pharmacology lab. I'm a software engineer working for an industry leader.

Once, she and the lab tech were having issues with their analysis program for a set of data. It was producing errors randomly for certain inputs, and the data "looked wrong" when it didn't throw an error. I came with her to the lab on a Saturday and looked through the spaghetti code for about 20 minutes. Once I understood what they were trying to do, I noticed that they had forgotten to transpose a matrix at one spot. A simple call to a transposition function fixed everything.

If this had been an issue that wasn't throwing errors, I don't know whether they would have even found the bug. I've been trying to teach my gf a basic understanding of software development from the ground up, and she's getting a lot better. But this does appear to be a systemic problem within the scientific community. As the article notes, more and more complicated programs are needed to perform more detailed analysis than ever before. This problem isn't going to go away, so it's important that scientists realize the shortcoming and take steps to curb it.

Great idea, but it doesn't work with multiple account signin (it crashes Chrome).

I agree with you, but I think the spirit of the article is to acknowledge the value of bitcoin as a technical solution to a problem we thought was simply unsolvable.

It probably shouldn't have gone into the economic value of bitcoin specifically, since it doesn't address most of the economic arguments against bitcoins.

This is a short-sighted analysis. Microsoft doesn't only make money from the Windows Phone licenses it sells. It makes money from advertising in apps, people using Bing, etc. Unfortunately an outside-in analysis of that is more difficult.

First of all, I've wanted to write a post like the OP's blog post for a while, but haven't gotten to it. Mine was going to include more math about deflationary spirals.

It seems that most commenters here are nitpicking the OP's individual points mostly due to their snarky/inflammatory wording and due to imperfect analogies like the comparison to the gold standard.

No, bitcoin isn't exactly like the gold standard. However, does it peg the value of the currency to an invisible standard (the money supply curve [mining])? Yes. Yes it does. Does this remove any and all flexibility from the currency? Yes. It is, in fact, bitcoin's decentralization that is its core weakness. It makes it impossible to expand the economy without devaluing the currency (see wikipedia for deflationary spiral). Transaction fees don't count, since they don't expand the money supply: they simply help the mining metaphor continue when the injection curve has been exhausted (by redistributing, not creating).

One of the commenters on Quora linked to an academic paper providing a solution to this problem. It was apparently published in ACL-HLT this year.

http://www.cs.washington.edu/homes/brun/pubs/pubs/Kiddon11.p...

Enjoy. It's easily the most hilarious academic paper I've read.

This would be such an incredibly stupid security failure.

Passwords should always be salted and hashed.

Credit card info should always be HSM-protected so that it is irretrievable except through a hardware API.

What was Sony thinking!?

What does this provide that glassdoor.com doesn't?

*edit: other than the app-ness, of course.

I guess my conclusion here is that just like most of the problems I see in the U.S. socio-econo-political system, the issue is rooted in money. The system is so biased toward allowing those with money to exploit those without, that it makes me want to go back to Canada.

The system is so broken that I don't even know how to begin thinking about fixing it.

1) A PhD prepares you for academia. However, due to the market being flooded with PhD's, industry won't accept you for a research position without one, even if you don't need it. In a perfect world, a Master's should suffice if it gave you any lab experience at all (at least in science). If industry does accept you despite not having a PhD, your salary will be lower, your career will be capped, and you won't move as quickly through the ranks.

2) The incentives are in all the wrong places. Schools want funding. They get funding by writing grants, which requires research. They want to do the research as cheaply as possible so as to maximize how far each dollar goes. So, they have a very strong incentive to keep grad students in limbo as long as possible, delaying graduation. Since grad students often have major loans left over from undergrad, and the additional degree keeps them from having to make payments, they'd rather be stuck in grad limbo for years than be stuck without a job. This is especially true since student loans (both public and private) in the U.S. are inescapable (you cannot bankrupt your way out of a student loan).

3) Even afterwards, really badly paid postdoc positions keep you in academia for 3-4 more years before you can do anything with your education. It's almost indentured servitude with the "promise" of a better future (by the time you're 35). Unlike MD's who actually have a good salary in sight after they graduate, PhD's (after several postdocs) can only hope to make up to $120-130k after all is said and done (unless they climb corporate ranks in industry).

4) Research is fraught with politics. Instead of trying to actually contribute to the human knowledge pool, you compete with other labs for funding, for research (to be the first one that discovers something), and for spots in the best journals. When you discover a neat paper, it's a game of "what can I do bouncing off of this research that will get me published in an awesome journal" instead of "let's collaborate with this lab, leveraging our strengths to contribute to human progress". Quite often, several labs are running the same experiments just because they want to be the first to make a critical breakthrough. Competition can be great, but it can also result in wasted effort and bitterness at life.

Or you can use cgdb (http://cgdb.sourceforge.net/), which has syntax highlighting and Vim keybindings.