Henrique - this is super cool. Really fascinating and inspiring to follow your success.
Unrelated to today's announcement, but curious if you could share a bit about your origins in "making a new credit card from scratch" at all: forming a relationship with a bank, card network, etc.
How difficult was it to even enter the space at all - any top takeaways or learnings? Non-obvious struggles you may have had to overcome?
For those who were perhaps intrigued, as I was--here is a bit more information I found through a cursory search about how Airbus's consensus system works. Interesting stuff. [0][1]
Regarding Xerox scanner compression issues, compare this great CCC-talk by David Kriesel, "Traue keinem Scan, den du nicht selbst gefälscht hast" [0] – Sorry, German only.
> DeFrancis’s argument to this effect turns on examination of an example quoted in Sampson (1985: 28‑9) of purported complex semasiography, the ‘Yukaghir love letter’. I had taken this example from a well-known book on writing, Diringer (n.d.: 35), and I retailed Diringer’s explanation of it without trying to check this. DeFrancis has done the discipline a considerable service by investigating the history of the example in detail, and it turns out to be something rather different from what Diringer and I described, and arguably not an example of ‘communication’ at all.
It seems nearly certain that this image is not what it was presented to be.
Yes, looking at the network requests I also get this error fairly consistently by the third or fourth batch:
> {"ApiResponse":{"$":{"Status":"ERROR"},"Errors":[{"Error":[{"_":"Too many requests","$":{"Number":"500000"}}]}],"Server":[""],"GMTTimeDifference":[""],"ExecutionTime":["0"]}}
Which then results in "Uncaught TypeError: Cannot read property '0' of undefined".
I would assume any API like this would have rate limits of some sort. If you are making a separate request for every TLD that is likely to be worse too.
I put this together as a fun little side project after beginning to wonder about geographic biases present in Wikipedia articles. Here are just a few comparisons that I've tried & found at least mildly interesting...
Here's an album of screenshots http://imgur.com/a/wmsLX, if you don't mind losing the ability to zoom in and look around :)
All the code is open source and available on GitHub https://github.com/theopolisme/wikipedia-contributor-locatio.... The tool uses a Python backend to access the Wikipedia API and pull a list of revisions for the given articles, then look up their locations using MaxMind's free GeoIP database. On the frontend side of things, I used leaflet.js and a custom-modded (to allow for variable point radii to indicate multiple edits from the same location) version of leaflet.heat to draw the map.
I put together a little imgur album with some examples from my own Location History: http://imgur.com/a/qLm1Q (I'm sure yours are much more interesting, though!)
location-history-visualizer is tool for visualizing your complete, consolidated, collected Google Location History. It works directly in your web browser – no software to download, no packages to install. Everyone deserves to know what data is being collected about them, without having to fiddle with cryptic pieces of software.
The only suggestion for improvement I can offer is to think through if it makes sense to "renormalize" the heatmap when I move the map or zoom the map. The current "normalization" has two for me unexpected effects:
a) My home and office is not colored "warmer" than many other places in my home town, although I bet I spend 90% of my time in those two places, and
b) I can see that I've been e.g. to Vienna, but when I zoom in I can't see anything - presumably because I've spent so little time there compared to my home town.
Some sort of "renormalization" of the heatmap would probably "fix"/change that.
Unrelated to today's announcement, but curious if you could share a bit about your origins in "making a new credit card from scratch" at all: forming a relationship with a bank, card network, etc.
How difficult was it to even enter the space at all - any top takeaways or learnings? Non-obvious struggles you may have had to overcome?