How are you using it for data crunching? That’s an honest question, based on my experiences with AI I can’t imagine how I’d use them to crunch data.

So I always have to check it’s work to some degree.

That goes without saying. Every AI I’ve seen or heard of generates some level of garbage.

My point is that I strongly feel that the kind of “AI” we have today is much closer to bacteria than to cats on that scale. Not that an LLM belongs on the same scale as biological life, but the point stands in so far as “is this thing intelligent” as far as I’m concerned.

it’s not inconceivable it could happen in the next two generations.

I am certain that it will happen eventually. And I am not arguing that something has to be human-level intelligent to be considered intelligent. See dogs, pigs, dolphins, etc. But IMO there is a huge qualitative difference between how an LLM operates and how animal intelligence operates. I am certain we will eventually create intelligent systems but there is a massive gulf between what LLMs are capable of and abstract reasoning. And it seems extremely unlikely to me that linear algebraic models will ever achieve that type of intelligence.

Intelligence is just responding to stimuli

Bacteria respond to stimuli. Would you call them intelligent?

I don’t know, have you ever used JavaScript? I’ve run into some really fucking weird bugs. I’ve also spent hours trying to find the source of an error message only to discover the error message was lying and caused by some other error.

The only part of copilot that was actually useful to me in the month I spent with the trial was the autocomplete feature. Chatting with it was fucking useless. ChatGPT can’t integrate into my IDE to provide autocomplete.

The point is that AI stands for “artificial intelligence” and these systems are not intelligent. You can argue that AI has come to mean something else, and that’s a reasonable argument. But LLMs are nothing but a shitload of vector data and matrix math. They are no more intelligent than an insect is intelligent. I don’t particularly care about the term “AI” but I will die on the “LLMs are not intelligent” hill.

I’m the opposite. AI is best (though not great) at boring shit I don’t want to do and sucks at the stuff I love - problem solving.

Their rules have stopped me from being able to do my job. Like the time the AV software quarantined executables as I was creating them so I literally could not run my code. When security enforcement prevents me from working, something needs to change.

My comment game has gotten far better since I started doing live code reviews. Essentially I ask myself, “Would I feel the need to explain this to someone during a code review?” and if the answer is yes I add a comment.

That’s a hot take. If you want your code to be maintainable at all, it needs comments. If you’re part of a team, write comments for them. If someone else may take over your project after you move on, leave comments for them. And have you ever tried to read uncommented code you wrote a year ago? Leave comments for yourself.

The key difference is that compilers don’t fuck up, outside of the very rare compiler bug. LLMs do fuck up, quite often.

Copilot frequently produces results that need to be fixed. Compilers don’t do that. Anyone who uses copilot to generate code without understanding how that code works is a shit developer. The same is true of anyone who copies from stack overflow/etc without understanding what they’re copying.

hackthebox is essentially a puzzle solving platform where the puzzles are designed to teach you hacking. You’re not supposed to hack the platform.

If I designed the schema it is most certainly going to be structured. Unstructured databases are awful.

async/await infecting all of my code, being unable to create a get myField() method that involves a hash calculation. It may be standard to do heavy lifting concurrently, but async hash functions are certainly not standard in any of the languages I’ve used (which is quite a few).

So you’re arguing that “Object oriented” shouldn’t apply to languages that are oriented around objects?

Of course, but OOP is typically about putting methods on classes, inheritance of behaviour etc.

You’re referring to one subtype of OOP. That may be what most people mean when they say OOP, but that doesn’t make it correct. Object-oriented programming is programming with objects, which does not require inheritance or classes.

I’ve done a little bit of Python in the past, the biggest thing being an automation task that borderline became an app. I certainly can imagine using it for scripts, though I default to bash because that’s almost always available but TBH mostly because inertia. Beyond that my default is Go because inertia (and I love Go). I watched a video by the Primeagen (on YT) - in his view, Rust is better for text/data pipelines and CLI tools. Being very familiar with Go and not at all familiar with Rust, that’s an interesting take because honestly writing a CLI in Go is kind of meh.

so you have to catch all exceptions then do extra work to tell what the specific situation is

That’s horrifying. That’s a solid reason to avoid Python like the plague.

For references within a scope, you’re probably right. For references that cross scope boundaries (i.e. function parameters), they necessarily must consume memory (or a register). Passing a parameter to a function call consumes memory or a register by definition. If a function call is inlined, that means its instructions are copy-pasted to the call location so there’s no actual call in the compiled code.