The compression is basic run-length encoding, leveraging the Perl repetition operator (x), and the property of the Perl print/say functions that they concat items passed in a list before writing to STDOUT.
I tried xz -9 on it and found, to my surprise, that it was actually longer than RLE!
Then I tried gzip -9, because perhaps that has a smaller header? Yup, saved a few bytes, now it's about the same size. Finally, I remembered that bzip2 does a lot better on text than gzip, and who knows, it might also have a shorter header than xz. Again, a few more bytes saved! Down to 223, where the original is 249 bytes (including the 'say' part but excluding the unnecessary delimiting apostrophes or the rest of the command).
Probably the best citation is a remarkable, rigorous paper by Chetty et al (2014) that uses individual IRS returns [1].
To quote those authors: “We find that children entering the labor market today have the same chances of moving up in the income distribution (relative to their parents) as children born in the 1970s. However, because inequality has risen, the consequences of the ‘birth lottery’ – the parents to whom a child is born – are larger today than in the past.”
The portrait of the college grad painted in the article is consistent with what I’ve seen as an undergrad at Harvard in econ and CS circles.
> [College students want money, structure, and sex appeal.]
But I’ll add another motivation to the laundry list, that draws smart grads to selective/prestigious programs (including Harvard, Goldman, Google, and even YC): Smart grads want to be surrounded by other smart grads, because they want to build peer relationships with future co-founders and business partners.
Yes most of the graduates from the top 10 universities and probably 100% of the ones who go for IB are not insecure.
The only ones are the 1% for come from poor backgrounds and managed to get a place on merit and who haven't learnt to fake it and are conflicted about changing social class
This article considers hedge funds in the aggregate, which seems to me to be a fallacy. It doesn’t consider variation within a category which we can usefully select against.
“Money in hedge funds is a bad investment” seems similar to saying “going to college is a bad investment,” when the value of a college degree is highly dependent on institution and major. CS at Stanford may be a fabulous investment, while Folklore/Mythology at U of Phoenix may not be.
I assume “ACCESS GRANTED” is preferred over your root prompt because it is more legible to the vast majority of viewers.
In fact, I suspect one noble goal in ItsAUnixSystem-style sequences is making sure everybody watching understands what’s going on: The access was granted, dummy.
Of course sometimes that’s gonna conflict with realism.
> The only real restriction is that fast lanes can’t be offered exclusively to a company also owned by the cable or phone company.
This fast lane already exists, and it exists for the cable company itself.
E.g. Comcast’s digital television (including Netflix-rivaling “Xfinity” on-demand service) is delivered over bandwidth that is dedicated/statically allocated to serving their entertainment package.
Worse still, Comcast’s data also has a dedicated backhaul. Live TV is collected from satellite feeds at a local “headend” facility, and on-demand content is likely cached close to the user à la Netflix Open Connect.
You can get a passport the same day in the US. Most but not all State Dept. “passport agencies” [1] require proof of international travel in the next 2 weeks.
I know, because I had one made in Atlanta, the day before a trip to Europe.
No, because “blurriness” (low local contrast) may indicate something besides a particular depth.
Consider, for instance, a head-on photograph of a print of a shallow-focused photo. The region that print embodies will have plenty of variation in contrast, but exist at a single depth. Also, consider that blurring increases in both in front of and behind the center of focus; how could we tell which depth the blurring indicated?
Something similar to what you suggest is, however, done in software autofocus, which can take repeated samples at different focal distances to clear things up. Maybe that’s something to think about, e.g. for a static subject. http://en.wikipedia.org/wiki/Autofocus#Contrast_detection
Yup, there's no simple way to recover depth from blur: there will be featureless regions where you can't tell if there was any blur -- in other words, there is no universal way to tell if a region has gone through a low-pass filter or if it is natively low frequency.
Would heuristics work well? I can think of a handful, but none really good.
https://en.wikipedia.org/wiki/Run-length_encoding
https://perldoc.perl.org/perlop.html#Multiplicative-Operator...
https://perldoc.perl.org/functions/say.html
https://perldoc.perl.org/functions/print.html