Any good links? I briefly looked up that it models fire, electricity, cutting etc. interactions, but if you put this in the frame of a text adventure rather than a 3D action adventure, would it be fun? e.g. typing "shoot arrow at explosive barrel" isn't as engaging as aiming the arrow yourself.
Would it make sense to think of this as a compact syntax for numpy? When it comes to array operations, are there differences that go deeper than the syntax?
KlongPy has a lot of other features beyond pure NumPy operations (such as IPC and web server), which you could see as a kind of making use of array operations in some application. You could look at the core Klong language as what you suggest.
You can do realtime in the sense that you can build Numpy arrays in memory from realtime data and then use these as columns in DuckDb. This is approach I took when designing KlongPy to interop array operations with DuckDb.
Friend of mine worked used to block off his friday afternoons for 'weekly review'. Which was part big thinking, part end of week nap, and mostly avoiding colleagues who had tricky tasks 'needed first thing monday' they had forgotten to bring up before.
It depends what the book is. For science fiction (or fantasy) stories like this, it's pretty common. And many are actually pretty active on social media as well.
Probably the most well known example is Neil Gaiman who is extremely active on tumblr, at least prior to Elon used to be extremely active on twitter, and would regularly drop into discussions of their works.
Other notable examples (albeit less active) off the top of my head include James S.A. Corey (Daniel Abraham and Ty Frank) and Andy Weir.
Just yesterday, my spouse was unpacking and came across a stack of envelopes containing correspondence I had received from authors I'd written to as a kid. I know then it felt really magical to have them write to me, especially since most of them were actually hand-written and discussed what I said meaningfully.
I don't remember it being a result of a teacher prompting me, though I suspect it was. They weren't books I read in school, but perhaps a teacher asked us what books were our favorites and had us send out letters. They're all laminated, too, which makes me think the teacher(s) took them and preserved them for us.
The only celebrity mail I recall writing, definitely as a class requirement, was to Carl Sagan. I was very disappointed to receive a form letter from his secretary in response.
Whenever I read a good book, see a great film, or appreciate an art piece, I try to track down the creator to send them a note of thanks. I'd say maybe 30% reply?
That said, I can't imagine creating something that people are still directly impacted by 60 years later. Software just doesn't seem to work like that
I do this with bands I really like, particularly newer groups whose first "hit" I cannot get out of my head. Few respond, but the point is I directly give them more money than they'd get through their label's playcount.
Hint to artists: put up a bitcoin receiving address on your portfolio (it'd make it a bunch easier).
Elie Wiesel responded to one of my specific questions [in his classroom response letter, decades ago]. Very powerful moment (hopefully not staged by my great English teacher of yesteryear).
Amazing huh? Me and my daughter finished this Dutch bedtime story book, and we wrote the artist to to tell him how much we liked his work. We actually received a heartwarming reply back, in which he gracefully accepted the compliment, and wished us well.
Arthur Whitney is showing how to build an array language using C in array language form.
AW is known for kdb+ which is often used in finance due to its extreme performance properties and ability for quants to quickly explore ideas.
Personally, to get a better handle on how array languages worked, I implemented KlongPy which is a python implementation of Klong, which descends from K (which AW wrote).
You have to play with this stuff to understand it intuitively.
Ha! For those of us who were in the Morgan Stanley Fixed Income group for many years in the 1990s and 2000s AW is known for APLus which was used extensively for modeling and application work.
There were a lot of different and kind of weird attempts at this in the industry. The basic problem is that recalculating DAGs and monte-carlo simulations using a ton of floating point math was extremely expensive. Excel was way too slow, C++ required expert programmers and much better organization of programming teams to figure how to coordinate cached intermediate values. MS went with APL, which reduced a lot of the boilerplate and allowed for relatively easy memoization. GS went with SecDB which treated computation as memoized DAGs. Not sure what the others did
FWIW, kdb+ is not that extremely performant - there's a lot of things that could be faster, and a lot of limitations that mean that you often would be better of not using a DB at all (or to use another DB and just pull everything you might need into memory). There is/was a tradeoff in that many things that would make it faster would require more code, and a cool thing about q/kdb+ is that it takes so little code you don't have I$ issues, but I think that's a tradeoff that doesn't make as much sense anymore in 2023.
What it's really great for is that it's really neatly integrated into the q language, which is great for exploratory programming, and it's fast enough not to get in the way.
I've encountered this idea that k's terseness somehow improves instruction cache use before. Can you explain further? It seems nonsensical, since instruction caching is about machine code, not source code. Why should it use the instruction cache better than any other JIT? Or is it interpreted, in which case "the terseness of the language improves cache use" might seem more of an admission than a boast... :-)
Thanks the insights. Not to over do self promotion, but aside from learning, the main reason I made KlongPy was to allow for optionality with the ecosystem. Use Klong for array operations and other libraries for standard stuff.
