I would probably prefer this, because then I could actually look up the unfamiliar terms and have some hope of eventually figuring out what the equation meant, instead of being brought up short and stumped by inscrutable notation.
I would probably prefer this, because then I could actually look up the unfamiliar terms and have some hope of eventually figuring out what the equation meant, instead of being brought up short and stumped by inscrutable notation.
If I am thinking about any problem, its outside the scope of any programming language in the first place. My point is, modern functions already make array manipulations simple enough. Even if you're doing something like coding LLMs from scratch, numpy, list concatenations, list comprehension, lambdas, stream/map/reduce all exist and its not nearly an issue to implement them, as is the case for writing assembly vs python.
The prime example in python for example looks like this: all(x % i != 0 for i in range(2, x)) This pretty much does the same operations in the same order on the same fundamental data structure, so I just don't see what's fundmenetally different about the Klong way of thinking.
Anyway, I don't mean to argue, if it works for you great, I wish I had something new
If I am thinking about any problem, its outside the scope of any programming language in the first place. My point is, modern functions already make array manipulations simple enough. Even if you're doing something like coding LLMs from scratch, numpy, list concatenations, list comprehension, lambdas, stream/map/reduce all exist and its not nearly an issue to implement them, as is the case for writing assembly vs python.
The prime example in python for example looks like this: all(x % i != 0 for i in range(2, x)) This pretty much does the same operations in the same order on the same fundamental data structure, so I just don't see what's fundmenetally different about the Klong way of thinking.
Anyway, I don't mean to argue, if it works for you great, I wish I had something new
That's a good way to put it. It's pretty hard to convey this to someone who hasn't actively tried and solved real problems in such languages though. You don't realize how much the "words get in the way" (as Granny Weatherwax would say) until you give an array language a good chance.
Another pop-culture quote that resonated in this regard is from The Matrix:
> Your brain does the translating. I don't even see the code. All I see is blonde, brunette, redhead.
All I see is range, sum-over, divide. The symbols turn into the concepts directly in your head - not as conscious translation, but in the way I imagine Chinese or Japanese kanji characters translate directly in the head of a native speaker.
I wish APL derivatives embraced some of these ideas, and made their magic spells easier to parse visually, and to format for readability. I don't know how to achieve that easily. Mathematical notation took centuries to develop. It took quarter of a century for programming languages to normalize indentation. Maybe APLesque languages will eventually come up with a notation that's less impenetrable than APL / K / Q, but less verbose than Pandas.
>This allows one to think faster and further than they could encumbered but a heavier syntax.
How does the programming language limit your ability or speed of thinking, lest when the fundamental data types and operations are the same? The hard work is always knowing what to implement. Saving some keystrokes for reversing an array or whatever other array manipulation is hardly a game changer.
Not at a computer now, can't check.