On Thu, Nov 7, 2019 at 7:21 AM Abe Dillon <abedil...@gmail.com> wrote: >> None of your objections ring true. A simple example is had from >> mathematics. The integral symbol conveys and represents a concept. Once >> the practitioner is introduced to the definition of that symbol, what it >> means, he or she uses it. It really is a simple as that, this is how our >> brains work. That's how you recognize the letter "A" as to correspond to a >> sound and as part of words. This is how, in languages such as Chinese, >> symbols, notation, are connected to meaning. It is powerful and extremely >> effective. > > I don't think you understood the point about APL's arrow assignment operator > being counterintuitive in Python. In Python: variables are names assigned to > objects *not* buckets that objects are stored in. Using a notation that > implies that objects are assigned to variables encourages a broken > understanding of Python's mechanics. >
For the record, I actually don't think that this is much of a problem. We have notions of "assignment" and "equality" that don't always have the exact same meanings in all contexts, and our brains cope. The sense in which 2/3 is equal to 4/6 is not the same as the one in which x is equal to 7, and whether or not you accept that the (infinite) sum of all powers of two is "equal to" -1 depends on your interpretation of equality. You might think that after an assignment, the variable is equal to that value - but you can say "x = x + 1" and then x will not be equal to x + 1, because assignment is temporal in nature. People will figure this out regardless of the exact spelling of either equality or assignment. > As to the role of ML and AI in all of this: These are tools that will allow > greater abstraction. Assuming more symbols will greatly enhance programing in > the future is like assuming that more opcodes will greatly enhance programing > in the future. AI and ML, if anything, will allow us to define the problems > we want to solve in something much closer to natural language and let the > computers figure out how that translates to code. What kind of code? Python? > C++? APL? x86? RISC-V? Who cares?! > Agreed. I would suggest, though, that this isn't going to be anything new. It's just a progression that we're already seeing - that programming languages are becoming more abstract, more distant from the bare metal of execution. Imagine a future in which we dictate to a computer what we want it to do, and then it figures out (via AI) how to do it... and now imagine what a present day C compiler does to figure out what sequence of machine language instructions will achieve the programmer's stated intention. Here's a great talk discussing the nature of JavaScript in this way: https://www.destroyallsoftware.com/talks/the-birth-and-death-of-javascript AI/ML might well be employed *already* to implement certain optimizations. I wouldn't even know; all I know is that, when I ask the computer to do something, it does it. That's really all that matters! ChrisA _______________________________________________ Python-ideas mailing list -- python-ideas@python.org To unsubscribe send an email to python-ideas-le...@python.org https://mail.python.org/mailman3/lists/python-ideas.python.org/ Message archived at https://mail.python.org/archives/list/python-ideas@python.org/message/PFYPVNG4NJDJITUNXOZBMCS5OK6Q2ZSP/ Code of Conduct: http://python.org/psf/codeofconduct/
