It “just worked” for me as well… Until I got annoyed, wiped it tf out, installed linux, and learned about tiling wms/compositors (hyprland my goat) in the process.

Trust me, you’re one bad day away from becoming one of us in full capacity:)

didn’t Arabs also introduce zero?

I mean, yes, but note how the word algebra has arabic roots

it’s a cloud service. It gives you access to an api. It couldn’t care less about your GPU. Can be used on anything that is capable of internet connection. Specifically NIM has a max requests per minute restriction tho. Due to this, running ai agents on it would be a pain in the ass, but technically possible (still not as painful as local inference tho). And it still works fine for plain chats.

i guess my advice is misplaced, given the community name, but in case the goal is to get LLM inference for free, not necessarily a local one, you could try opencode (their free plan gives you access to some decent models), or nvidia’s NIM if you don’t want a vendor lock-in to any specific agent/chat app.

please buy some fruits and vegetables from time to time. Actually a lot of time. Different vegetables and fruit. Some nuts too. Eating the same meal every day is very unhealthy and can have very bad l andasting consequences for your health, especially in combination with stress (i know this from my personal experience of being poor and autistic unfortunately). And “hunger pains”? This is already very not ok.

Maybe start a gofundme campaign to at least temporarily somewhat mitigate the money problem? I’ll gladly send you a few bucks, if it helps you avoid what i got through.

[…] He used unproven error-prone technology […]

I’d say, there was plenty of time for people, including Linus, to understand its limits, especially considering that before introducing current AI policy to the kernel maintainers, he used it for his personal project.

Human-written code is just as error-prone and unreliable, even if it is written by the most experienced dev there is. Do i really need to explain that your own ability to write quality code varies, based off countless factors that affect your mental state? John Dev didn’t have his breakfast — boom! Uncaught race condition, segfault, or some other critical bug, or safety vulnerability is introduced into prod.

What i’m saying is, unreliability of the submitted code is a problem as old as coding itself. It’s a well known one, hence all the static analysis tools developed over the decades, code reviews, hell, even opensource itself partially exists to solve this very issue. The fact that the bugs were caught is the living proof of just that.

If Linus was as smart as you seem to believe […]

“Smart” doesn’t mean “omniscient”, doesn’t mean “makes no mistakes”. “Smart” is not some kind of divine status. He’s still human, he still gets tired, his focus still can dwindle, and important things still slip his mind.

The code looked good, he got fooled and here we are.

That’s your speculation, probably based off your own experience. Neither of us know the exact circumstances, by which the discussed bugs were introduced.

Ergo, you should leave as little places for AI to make mistakes, undiagnosable by static analysis tools, as possible. In other words, make all the technical and algorithmic decisions yourself.

i’m too autistic to understand, whether this is a sarcasm

[…] if a human makes a mistake it’s a learning opportunity.

As per Linux kernel AI policy (and a common fucking sense), you’re the one responsible for the code that is submitted from your side, regardless of the tools and pipeline you use. Now get this, when an agent makes a mistake, that you didn’t notice, that’s still a learning opportunity, especially when you’re held accountable for the fuck up.

Also, LLMs don’t necessarily generate good code. They excel at generating good-looking mediocre code.

True… When you give them a general task that involves solution of technical problems and decision making. But when it’s a concrete “do the x thing over here, using this, this, and this”, which is then accompanied by your manual review of the changes, they actually do fine, basically allowing you to minimize the tedium, while not robbing you of the most interesting and important parts of development.

Did Linus’s pipeline look like what i described, tho, when he introduced the aforementioned bugs? Was it his technical decision that, by proxy, introduced bugs? I don’t know. Regardless of the answers, he’s a grown-ass man, and thus is responsible for the consequences of his decisions.

Is he more likely to introduce a bug now that he uses AI? Only time will show. I might be wrong, but i think Linus is too smart for it to be the case.