Why Gentoo?

Multiple times in the past I’ve been thinking of how Gentoo is perceived by the wider public, the non-users. What probably stands out most is compiling. Almost everyone who heard of Gentoo knows it has something to do with compiling everything. And why are we doing that? Well, besides being hardcore, the common sentiment goes for performance. So yeah, Gentoo users must be some kind of hardcore ricers who try to squeeze every last bit of their system performance.

To be honest, I don’t think that’s a good way to describe Gentoo. Yes, compiling is at the core of it. But performance? I don’t think so, at least not in the obvious, -O9999 -fzomg-fast way. The world has moved on, CPUs have gotten faster, optimizations have gotten smarter, and distributions have started optimizing more aggressively. Optimization-wise, I suspect your average Ubuntu package with generic optimizations may be no slower than the equivalent Gentoo package fine-tuned for your CPU. And if it’s not, then it probably won’t make a real difference anyway.

There’s much more to Gentoo than that. Yes, some of it comes from building from source: the flexibility. But a lot of it comes from the wider Gentoo philosophy, the philosophy that brought us all together. The idea that Gentoo is the distribution we’re making for ourselves and people who enjoy Gentoo. So if I were to make a few arguments for Gentoo, I’d focus on that. And this is what I’d like to do here.

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The pinnacle of enshittification, or Large Language Models

Honestly, I hate that I read about LLMs all the time. I hate all the marketing bullshit, but also all the critical pieces. Not because the criticism is wrong. I hate them precisely because they’re right. And I hate the feeling that I have to write yet another piece on that same topic, to collect some of the thoughts I have had over the recent months.

Machine learning isn’t anything new. Neither is calling it “artificial intelligence”. Not only pop science writers and journalists, but even more technical folk have been using the term, and I never complained. I didn’t complain about games having “AI” either. It was always clear that this is a special use of “intelligence”, one far from what animals truly possess. This changed recently.

When LLMs enabled chatbots to use human language, the misuse of the term exploded. Obviously, the marketing people loved calling it “artificial intelligence”. The media, the users and the whole IT industry followed. Even people who knew better stopped bothering. On top of that, anthropomorphisms became commonplace. LLMs could be said to be “thinking”, “lying”, “hallucinating”, to “approve” or “disapprove”, “like” or “dislike”…

Perhaps it wouldn’t be so bad if not for the fact that LLMs are so good at imitating human intelligence. The problem is not really how people call them. The problem is that there is a number of people who start actually believing that their chatbots are conscious. And I can see why that would be happening…
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Money isn’t going to solve the burnout problem

The xz-utils backdoor situation brought the problem of FLOSS maintained burnout into the daylight. This in turn lead to numerous discussion on how to solve the problem, and the recurring theme was funding maintenance work.

While I’m definitely not opposed to giving people money for their FLOSS work, if you think that throwing some bucks will actually solve the problem, and especially if you think that you can just throw them once and then forget, I have bad news for you: it won’t. Surely, money is a big part of the problem, but it’s not the only reason people are getting burned out. It’s a systemic problem, and it’s in need of systemic solution, and that’s involves a lot of hard work to undo everything that’s happened in the last, say, 20 years.

But let’s start at the beginning and ask the important question: why do people make free software?

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