Vim + Pandoc + Beamer + pdfpc is also the best way to write Presentations I have found so far:

https://github.com/maxmunzel/talk-algorithms-for-np-hard-pro...

Great Work! One thing I noticed was that some Animations (Conductivity and Relative Rockets) move on iOS while scrolling. Others (Orbits, Spring-Mass System and Gravity) work fine...

Now they work as expected. Maybe it only occurs the first time you load the page...

Maybe, but its actually really good at not firing when you scratch your head, which is probably more common than casually waving at your webcam ;)

> And it also doesn't lose all your messaging history everytime your phone breaks.

There is no way to transfer Messages between iOS and Android or to backup messages in any way really - except of storing them plaintext at Google/Apple.

I'd be really thankful, if anyone had some solution for this...

I've successfully migrated from iOS to Android; just following the tutorial that the top Google results show work like a charm

"top Google results" is different depending on who's searching.

I did some testing on the same (kind of) dataset and task:

First test: A single 2.9GB file

time rg Result all.pgn | sort --radixsort | uniq -c 13 [Result ""] 1106547 [Result "0-1"] 1377248 [Result "1-0"] 1077663 [Result "1/2-1/2"] rg Result all.pgn 1.12s user 0.55s system 99% cpu 1.680 total sort --radixsort 3.87s user 0.37s system 71% cpu 5.911 total uniq -c 2.69s user 0.02s system 45% cpu 5.909 total

Using Apache Flink and a naive implementation It took 13.969 seconds.

Second test: same dataset, split between 4 files

time rg Result chessdata/ | awk -F ':' '{print $2}' - | sort --radixsort | uniq -c 13 [Result ""] 1106547 [Result "0-1"] 1377248 [Result "1-0"] 1077663 [Result "1/2-1/2"] rg Result chessdata/ 1.70s user 0.97s system 42% cpu 6.292 total awk -F ':' '{print $2}' - 5.47s user 0.07s system 88% cpu 6.289 total sort --radixsort 4.13s user 0.42s system 43% cpu 10.559 total uniq -c 2.73s user 0.03s system 26% cpu 10.559 total

Flink: 12.724s

Conclusion: For this kind of workload, both approaches have comparable runtimes, even tough taco bell programming has the upper hand (as is should for simply filtering a text file). It took me about equally long to implement both. I think both approaches have their use case.

I ran this locally on my Laptop with 4 logical cores.

Hadoop is very slow, because it persist the data to disk before every stage. You really wouldn't want to use Hadoop if you don't have a good reason too. More modern tools like Spark and Flink fare better there.

Maybe because the author lacks access to non-western cultures and doesn’t want to make unbaked claims? I’d personally had a hard time getting a feel for African/Eastern/etc societies.

The actual resolution of the human eye is much smaller than that and a lot of our perception is based on interpolation. It's pretty interesting to read up on this.

Yep, this. Each eye is ~1MP, but vibration increases spatial resolution.

Researchers are using this effect now with mobile camera sensors and can image on the 100 nm length scale using interpolation.

Well, without eye tracking you need to render the whole image at peek angular resolution and refresh rate.

I can recommend you to start with 5 minutes (set a timer), increase to 10. After some practice you can omit the timer, but it really helps you getting started.

I wrote a dpll (the standard algorithm for SAT) Implementation in Haskell, that’s also pretty straight forward: https://github.com/maxmunzel/dpll/blob/master/README.md

Feel free to ask any questions.

Thanks! I did a port of it and this could be my way in to discovering more about SAT solvers. (Doing ports is one of my preferred means of jumpstarting my motivation for more complex areas of study).

That reminds me of how great of a device my iPod shuffle was. To bad the battery died..,