Here's a different hot take: GPT/LLM/AI will eventually make all languages obsolete. You tell it what you want and it'll just output machine code directly.
It's like the joke:
The programmer's wife said: "Please go to the store and buy a carton of milk and if they have eggs, get a dozen."
He came back with 12 cartons of milk.
She said, "why did you buy twelve cartons of milk?"
He responds "they had eggs"
(there are rare features like this in some parsers, like dangling else, but they are considered design problems)
I tried to trick it into running an infinite loop by giving it an obfuscated recursion for "generating squares" and overriding the exception that stops it.
It informed me that the action would infinite loop (spotted it better than me) and suggested that I didn't need such a complicated structure to calculate squares. Then it proposed a tessaract formula that "is bound to the laws of physics".
This is a problem that humans struggle with too.
The two ways you typically end up getting around this problem with a programming language; a subset of natural language that uses very short and terse sentences with a simple and limited grammar;
BUY MILK(1).
IF EGGS EXIST THEN
BUY EGGS(12)
END IF
Locate, select, and acquire, through lawful means, one (1) carton of milk, being of a commercially reasonable grade, suitable for human consumption, and free from any defects that would render it unsuitable for its intended purpose; and
In the event the designated commercial establishment has available for sale, (12) one dozen eggs, the Designated Acquirer is hereby further empowered to purchase the aforementioned eggs, subject to them being in compliance with the prevailing quality standards for eggs.Language does not handle most business process nor efficiency goal and even security restrictions. People and logic do. Little of that language (!) is in the written word. It is done mostly by failures and historic-obvious-cultural practice.
Emulation does not mean 'comprehension' of all the purposes involved in craftsmanship of handling data for business or for even computation.
Most AI-solved problems are search reduction for spoon fed problem areas of data.
Some random things that seem difficult to get an AI to deal with:
1) Things that people expect you to know by observation, but not be told and not to say.
2) Things that people expect you to know/adhere to, in spite of being told something different.
3) Strategically creating the impression that you do or do not have the ability to change your course of action.
Punctuation problem.
Using natural language, it is incredibly difficult to make unambiguous statements. For most of the twentieth century, the problem was regarded as so severe that analytic philosophers would encode their most important points in symbolic logic. And it's not like we have one symbolic logic here; there are literally dozens of higher-order logics, each with their own syntax, and some of which are mutually incompatible.
Meanwhile, complex, difficult-to-master conlangs such as Ikthuil and Lojban have flourished in pockets of the philosopherse simply because they provide, essentially, the kind of clarity that any basic programming language provides.
I can easily imagine AI/ML inertia, as OP wonders about, and I can also easily imagine forms of e.g. Lojban, Ikthuil, or a mishmash of several higher-order symbolic logics becoming the basis for a new ML-informed programming language, but if your imagination has you talking to the computer the way you'd talk to a subordinate, in English or some other natural language, then do I have a monkey's paw for you.
If you don't think that's ever going to be possible with AI (notice how I used the word "eventually" in my post) then I don't know what to say to you.
I knew the AI hype machine was real but I didn’t realise it had replaced decades of computing security already.
That said, it doesn't seem to be outside the realm of possibility. Which is why I said it.