While I haven't gone too deep on that yet, I was thinking we'd take inspiration from how GitHub maps IdP groups to native GitHub teams. So first step here would be adding user groups/teams natively in the product.
While I haven't gone too deep on that yet, I was thinking we'd take inspiration from how GitHub maps IdP groups to native GitHub teams. So first step here would be adding user groups/teams natively in the product.
[0]: https://github.com/koekeishiya/yabai/wiki/Disabling-System-I...
I would be curious to see the ratio of swearing in comments vs code identifiers. I'd also be curious to see if the repos with swearing in their comments just have more comments in total. Perhaps the correlation is, "code with more comments is more likely to be higher quality".
edit: tutanota calendar also lacks search, but at least they have it planned. proton haven't.
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Near the beginning of a class, Professor Neyman wrote two problems on the blackboard. Dantzig arrived late and assumed that they were a homework assignment.
According to Dantzig, they "seemed to be a little harder than usual", but a few days later he handed in completed solutions for both problems, still believing that they were an assignment that was overdue.
Six weeks later, an excited Neyman eagerly told him that the "homework" problems he had solved were two of the most famous unsolved problems in statistics.
https://en.wikipedia.org/wiki/George_DantzigReminds me of that :)
edit: Here's a slightly more colourful telling of the story: https://www.snopes.com/fact-check/the-unsolvable-math-proble...
Does anyone happen to know which two problems Dantzig solved? Don't seem to be having much luck on my searches
"In 1951, David A. Huffman and his MIT information theory classmates were given the choice of a term paper or a final exam. The professor, Robert M. Fano, assigned a term paper on the problem of finding the most efficient binary code. Huffman, unable to prove any codes were the most efficient, was about to give up and start studying for the final when he hit upon the idea of using a frequency-sorted binary tree and quickly proved this method the most efficient.[5]
In doing so, Huffman outdid Fano, who had worked with Claude Shannon to develop a similar code. Building the tree from the bottom up guaranteed optimality, unlike the top-down approach of Shannon–Fano coding."
I wonder why it doesn't come up a lot in protein rich food discussion. I will try to read up more about it.
[1] https://ndb.nal.usda.gov/fdc-app.html#/food-details/168147/n...
I've used it for remote conferences, and I like its 2D UI. Real sense of space there.
Also you can see if other teammates are having a discussion or co-working in a common area, which made for some ad-hoc co-working sessions.