655 karma · joined February 6, 2014
I don't think this is true. The person in power can be wrong (e.g.) 10% of the time and you'd still have a mostly stable and tolerant system.
Yep! Article is a big improvement; first I saw the image was earlier today when it was tweeted on its own here: https://twitter.com/b0rk/status/1179449535938076673?s=20 and her images are often awesome because they capture nuance in a tiny poster
I'm really glad the accompanying article has a bunch of qualifications of the form "Database engines don’t actually literally run queries in this order" but a lot of the beauty of these diagrams is that they work on their own.
I wish the title of the picture said something more like "SQL queries are interpreted in this order" to make it clear we're talking about semantics and not what actually takes place.
This seems to match with the phenomenal experience of being overwhelmed in noisy or crowded situations, and of the difficult part of meditation being teaching yourself not to suppress experiences as they arise and just take everything in.
Rocket launches presently have a small effect on total stratospheric ozone (much less than 0.1%). Space industry developments indicate that rocket emissions may increase more significantly than reported in the previous Assessment. Their impacts will depend on rocket design (particularly the altitude of emissions), launch vehicle sizes, launch rates, spaceport locations, and fuel types. Important gaps remain in understanding rocket emissions and their combined chemical, radiative, and dynamical impacts on the global stratosphere and in projections of launch rates. These gaps limit the confidence level of predictions of present and future impacts of rocket emissions on stratospheric ozone and suggest periodic assessments are warranted. The lifetime of the most important rocket emissions is limited, and the stratospheric accumulation of rocket-emitted black carbon and alumina particles varies in correspondence with global launch rates and altitude of emissions.
The reason to use transducers instead of a for loop here is that it allows you to expose a library function which takes a transducer as input. It's hard to refactor the for loop above to allow someone consuming this function to specify additional things they want to aggregate due to an API change in the definition of the 'slang' type, but with transducers you just take one as an argument.
Does such a thing exist?
I remember seeing a modern and pretty website once that used SWI prolog and JavaScript to help you visualise natural deduction proofs but I can't find it anymore :'(
His real argument exists in a bunch of stuff he wrote about intentionality (the real argument probably still fails - but it's more nuanced than the Chinese room stuff everyone talks about).
If you want a really good paper about the problems around machines and minds check out "Troubles with Functionalism" by Ned Block
[1] The channel is great, everyone should check it out. https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw
For example
Root: KTB Kataba (he wrote) Kitaab (book) [thing you write] Maktaba (bookshop / library / office) [place you write] Kateb (clerk, writer, author) [writer] (and so on for words that don't translate directly into English)
Root: AML Amala: (he did / worked) Amal: (~action) [thing you do / make] Mamal: (factory) [place you do / make] Amel: (~worker) [doer, maker, worker]
So on for words like (kitchen = place where you eat, pilot = person who flies).
The previous comment arguing that Arabic is too rigid for new vocabulary overlooks how this rigidity allows for a very well structured grammar, that ability to express thoughts and ideas thag just fall out of a result of the combinatorics.
Similarly, this means that contrary to previous comments, Arabic is also /very well/ encoded for many tasks. Once you know your roots, is very easy to reverse engineer what a lot of commonly used words mean. What's more, you can (and people have) exploited this to write very efficient semantic compression algorithms for Arabic text.
You can't see it in the English letters but these transformations are super algorithmic, you do them by just doubling consonants or adding vowels and it's very intuitive for native speakers.
There are only about a total of 6000 lexical root words in Arabic, so on a computer you can represent each word by encoding it's lexical root, and the grammatical transformation on it. This results in compressed text which is also still very easy to analyse for meaning and sentiment.
You can check out the literature on Arabic natural language processing to see more like this, and a lot of them double as helpful tools for learning Arabic. Google once made an API which would take written Arabic text and infer the locations of all the pronunciation marks from the context and vocabulary, so you can turn text into a form that's easier for beginners to read. Yamli is a popular tool which automatically transliterates Arabic that has been written phonetically in Roman characters back to correctly spelled Arabic letters, so if you've heard a word but don't know how to spell it you can still Google it. I'm sure there are many other cool things I don't know about too.
There may be a lot of spoken dialects, but written Arabic is potentially one of the most standardised and carefully encoded languages there is.
https://chemistscorner.com/have-you-formulated-with-dry-wate...
I feel like all the best tutorials are written for people who are good with music but need to learn to code. Anyone out there have any good resources for using sonicpi to learn more music theory as a coder?
Breifly, it's the idea that being perfectly rational, is, in practice too resource intensive for us to do all the time - so the /actually/ rational thing for us to do is to use heuristics and folk-concepts in our day to day lives, rather than totally philosophically sound methods of reasoning.
Always argue for your weakest crux. I.e. out of all the necessary premises of some position you hold, always keep the hardest to defend premise close to the front of your mind.
This is counterintuitive because people reflexively try to bury their weakest assumptions. What's more: we're rewarded for presenting strong arguments. But if there's some fact that, if disproven, would cause you to change your mind and you aren't really confident that that fact is true - you should care the most about finding out if it's false, or at the very least becoming more certain in your belief about it.
The "double" part of double crux means that the crux you choose has to be a crux for both people, i.e. if it's established either way, that alone has to be sufficient to convince both people of the overall argument being true or false.
If you pick a crux that is a truly provably untenable position, and it turns out to also be a crux for the other person then they should happily change their mind on seeing the proof. If they don't it's not like they're committed to saying you've "won" against their will or anything, at worst it turns out that the crux they agreed on wasn't really a crux for them after all. At best, they discover that their belief rested on an untenable position.
By design it's pretty hard for a malicious actor to play double crux to win without also playing it to discover the truth, so long as they actually choose honest cruxes for themselves (and to some extent, even if they don't).
(Except maybe the template / type system examples - I hear that's a lot like programming in Haskell)