I am slowly trying to figure out Nix/NixOS. I just realized something I'm very confused by: Is it really the case “pinning’ in NixOS prototypically means “pinning a single version of the entire package repository, and then pulling in whatever versions it contains”? I mean, "it's all just code" and it seems to be *possible* to mix and match via `fetchTarball`. But is pinning the universe as-a-unit really the normal pattern?
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But life, if we're lucky, is very long. We have plenty of time to try different things, to live different lives, to be confused, and figure things out, and then be confused again.
Maybe Nix is like Rust: Amazing if you don't have to look at the code! I'm open to the idea that Omarchy Cinque could switch packaging system if I never have to look at nixlang, there are no ergonomic regressions, and we have full repo sovereignty.
you just you can't base your business decisions based on what everyone else is saying around you. Like, if you go too much with the herd, you will get immensely confused and you will end up nowhere. And so you have to develop your own compass of what you think the future is going to look like because everyone else will just confuse you.
LLMs themselves are the perfect captive reader: they never get bored or confused, never miss a reference or have an emotional reaction, never ask themselves why am I reading this?, never close the tab.
Which brings me to the film adaptation of Inherent Vice, that widely-disliked, subtly-championed shaggy stoner LA noir that confused critics and rankled fans and also happens to be the best movie Paul Thomas Anderson has ever made.
I’m also still not sure how much I like nix – it’s very confusing! But it’s helped me compile some software that I was struggling to compile otherwise, and in general it seems to install things faster than homebrew.
Their words now
I’ve mostly switched back to Homebrew, nix was interesting but overall I think it’s not worth the complexity for me
So most people, when they advertise new context window increase, they talk a lot about finding the needle in the haystack sort of evaluation metrics and less about whether there’s any degradation in the instruction following performance. So I think that’s where you need to make sure that throwing more information at a model doesn’t actually make it more confused.
Even in that case, though, what we should trust is not the particular output of the scientific process at any given time. It can make wrong turns. Instead, we should trust that it will find the truth eventually, and that it is our best and only method for doing so.
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