Two quotes the hosts brought up stuck with me:
(at 15:05) "A language that doesn't change the way you think is not a language worth learning". From Alan Perlis [1], and his Epigrams in Programming (#19) [2]
(at 16:49) "it is a privilege to learn a language/ a journey into the immediate". From poet Marilyn Hacker [3]; totally captivating idea, even if not not about programming languages [4]
[1] https://en.wikipedia.org/wiki/Alan_Perlis [2] https://cpsc.yale.edu/epigrams-programming [3] https://poets.org/academy-american-poets/winner/prizes/james... [4] https://www.enotes.com/topics/marilyn-hacker/critical-essays
us:{$[#i:&{(y~*K)&"*"~\*x}':x;@[x;i;:[;,"_"]];x]}
[1] Real example found in a random script on https://nsl.com/: http://nsl.com/k9/sql.k
It's like someone threw up the noise that modems make during initial connection onto an electric typewriter from the 1960s, and then explained their intention using quotes from a Lovecraft novel.
The jump from Python to Haskell - or really anything along that way is like talking about a ladder of computing. You start at one end, and you are climbing upwards. And every step you take, you can look down and see all of the things you knew before, but with greater perspective.
And Haskell? Well, it's definitely pretty far up the ladder. If you get Haskell, you feel like you really understand what's going on. I know pg was talking about lisp when he was thinking blub, but in some blubish respects, Haskell is a better lisp than lisp.
But see, going from Haskell (or really anything) to Iverson is like, listen: Forget the ladder, because a ladder only goes up and down. Iverson is sideways. It is in this way, like adding depth to flatland, that Arrays are an even bigger deal than you can possibly imagine until you go there.
I can't believe why it feels so hard? !I already know pascal and obj-c and F#!, kind of similar, no?
Now I feel rust so easy (as python easy!) that is weeeeeeird. (btw: I think is months now where I never think I have meet an error or situation that truly confuse me).
Instant subscribe from me.
So this thread's podcast of 52 minutes of a complex technical topic with multiple speakers could cost ~$200. A programming-related podcast is already a niche topic with a tiny audience and an Array Languages podcast is an even tinier subset of that so the cost might not be justified.
I suppose podcasts could be uploaded to Youtube and let their speech-to-text algorithm do an auto-transcribe. However, the A.I. algorithm is not good at tech topics with industry jargon/acronyms and the resultant transcription will be inaccurate.
That's a great feature! But it also highlights the limited accuracy of the AI machine learning algorithm for technical topics with jargon. E.g., at 27m00s, the caption algorithm incorrectly transcribes it as as "APL is joked about as a right only language" -- but we know the speaker actually said, "APL is joked about as a write-only language". And the algorithm incorrectly transcribes "oversonian languages" when it's actually "Iversonian languages".
The algorithm also doesn't differentiate multiple speakers and the generated text is just continuously concatenated even as the voices change. Therefore, an audio-impaired wouldn't know which person said a particular string of words.
This is why podcasters still have to pay humans (sometimes with domain knowledge) to carefully listen to the audio and accurately transcribe it.
I hate this. What were they thinking about? Why not a damn text file that people can grep?
sep=:10#.^:_1] NB. Separate digits
ea=:&.> NB Perform on each
sep ea 23 7534 322 7 24756 #ea n NB. How many? +/ea n NB. Sum */ea n NB. Product /:~ ea n NB. SortOne of the presenters is a novice with c++ background and the rest all are experts in their respective array programming languages.
In any financial centre there are hundreds of (often very well-paying) jobs using these languages (well mainly k and its ilk).