If something uses a lot of ifelse statements to do stuff like become a “COM” player in a game, it is called an Expert System.
That is what is essentially in game “AI” used to be. That was not an LLM.
Stuff like clazy and clang-tidy are neither ML nor LLM.
They don’t rely on curve fitting or mindless grouping of data-points.
Parameters in them are decided, based on the programming language specification and tokenisation is done directly using the features of the language. How the tokens are used, is also determined by hard logic, rather than fuzzy logic and that is why, the resultant options you get in the completion list, end up being valid syntax for said language.
Now if you are using Cursor for code completion, of course that is AI.
It is not programmed using features of the language, but iterated until it produces output that matches what would match the features of the language.
It is like putting a billion monkeys in front of a typewriter and then selecting one that make something Shakespeare-ish, then killing off all the others. Then cloning the selected one and rinse and repeat.
And that is why it takes a stupendously disproportionate amount of energy, time and money to train something that gives an output that could otherwise be easily done better using a simple bash script.
I am not talking about what it does, I am talking about what it is.
And all tools do tend to replace human labor. For example, tractors replaced many farmhands.
The thing we face nowadays, and this is by no means limited to things like AI, is that less jobs are created by new tools than old destroyed (in my earlier simile, a tractor needs mechanics and such).
The definition of something is entirely disconnected from its usage (mainly).
And just because everyone calls LLMs now AI, there are plenty of scientific literature and things that have been called AI before. As of now, as it boils down all of these are algorithms.
The thing with machine learning is just that it is an algorithm that fine tunes itself (which is often blackbox-ish btw). And strictly speaking LLMs, commonly refered to as AI, are a subclass of ML with new technology.
I make and did not make any statement of the values of that technology or my stance on it
I mean doesn’t it heavily depend what you refer to as AI?
ML algorithms, come very close to LLMs and have been back in the day refered to as AI. They are also used in code completion.
Also both of these are algorithms, but with weights defined by data input.
You seriously misunderstand what the acronyms you’re using refer to. I’d suggest some reading before commenting, next time.
If something uses a lot of
if elsestatements to do stuff like become a “COM” player in a game, it is called an Expert System.That is what is essentially in game “AI” used to be. That was not an LLM.
Stuff like
clazyandclang-tidyare neither ML nor LLM.They don’t rely on curve fitting or mindless grouping of data-points.
Parameters in them are decided, based on the programming language specification and tokenisation is done directly using the features of the language. How the tokens are used, is also determined by hard logic, rather than fuzzy logic and that is why, the resultant options you get in the completion list, end up being valid syntax for said language.
Now if you are using Cursor for code completion, of course that is AI.
It is not programmed using features of the language, but iterated until it produces output that matches what would match the features of the language.
It is like putting a billion monkeys in front of a typewriter and then selecting one that make something Shakespeare-ish, then killing off all the others. Then cloning the selected one and rinse and repeat.
And that is why it takes a stupendously disproportionate amount of energy, time and money to train something that gives an output that could otherwise be easily done better using a simple
bashscript.No because AI replaces a human role.
Code completion does not replace a human role, that’s like saying that spell check is AI.
I am not talking about what it does, I am talking about what it is.
And all tools do tend to replace human labor. For example, tractors replaced many farmhands.
The thing we face nowadays, and this is by no means limited to things like AI, is that less jobs are created by new tools than old destroyed (in my earlier simile, a tractor needs mechanics and such).
The definition of something is entirely disconnected from its usage (mainly).
And just because everyone calls LLMs now AI, there are plenty of scientific literature and things that have been called AI before. As of now, as it boils down all of these are algorithms.
The thing with machine learning is just that it is an algorithm that fine tunes itself (which is often blackbox-ish btw). And strictly speaking LLMs, commonly refered to as AI, are a subclass of ML with new technology.
I make and did not make any statement of the values of that technology or my stance on it