antioedipus

First of all, many rolling release distros don’t follow upstream as fast as possible—there’s often some testing window.

People go on and on about backported security patches and stability, but I’ve had to handle so many buggy patches or issues that never got a backported fix that I now think this is basically a fantasy. The distro maintainers just don’t have the time (or experience with all the software they ship!) to backport patches for every single issue. I’d really rather get a fix by the actual software maintainer than a year-old mystery meat version that still has a bunch of known non security bugs fixed in upstream that the distro maintainers don’t care about.

Even worse, being able to stay on essentially outdated software puts a lot of organizations into a tough spot when their LTS version finally becomes unsupported. Practice makes perfect, and I think lots of small, regular updates result in a lot less pain than a mega-update every few years (really: I’ve had to manage one of these more than once, and it’s a total nightmare figuring out which of 1000 changes in the new LTS version caused a performance regression or something).

For something with “math” in the title, this article sure has a lot of basic statistical mistakes (like, things you learn not to do in an intro course).

* You can think of it as a factor graph with linear residuals and Gaussian noise functions in factors that connect a chain of variables, with all but the most recent variable marginalized. It’s a well known fact that linear, Gaussian factors result in a closed-form expression that gives the optimal maximum a posteriori estimate. The Kalman filter exploits this very special case. You can also write a LQR down with a factor graph (as the parent commented, the KF and LQR are duals).

Also, why run all of Microsoft’s spyware and deal with their forced updates just so you can get through to a slightly slower and less compatible version of Linux.

This website never fails to amuse me…

What is the intention of this comment? That Debord is “far right” or a reactionary? That people who read him are? That it’s interesting that a Marxist philosopher is read by reactionaries?

I am about the age of the people this article is talking about. This is laughably out of touch. Take a look at the right communities on TikTok or Instagram or Discord (they’re not small) with people aged around 13-20 and you’ll see that Marx to Mao to Deleuze to Fisher are alive and well in the minds of today’s young people. There are people my age who are reactionaries, but there are more who want out of the late-capitalist hellscape that’s been foisted on us.

I’m not even sure where to start with this because it’s such a vulgar misreading of Hegel… Hegel generally rejected the “thesis, antithesis, synthesis” triad (which mostly comes from Fichte.) Dialectics, and his overall system of immanent critique, have considerably more subtlety and complexity than the determinism and teleology that you suggest. An even cursory reading of any of Hegel’s major works reveals how entirely misplaced most of your post is. I agree that a lot of Hegel’s political philosophy is marked by naivete, but this doesn’t mean his system can be rejected wholesale. That we should avoid this wholesale rejection in the face of apparent contradictions is actually one of Hegel’s basic points!

It’s good to have something like this. Last time I worked with libav the only available good documentation was the official examples and the ffmpeg (the tool) source code itself, along with the comments in the headers.

Yep. Animals are the most common way that diseases are introduced to humans, and industrial animal agriculture brings these animals into close proximity with themselves and us. Removing animal products from our diets not only mitigates this huge disease reservoir but also removes a huge source of greenhouse emissions, land use, pesticide use (for feed), and animal and labor exploitation (the meatpacking industry is extremely exploitative in the United States.)

An interesting side point is that the graph optimization approach used here is somewhat similar to modern graph-based visual SLAM

The graph in the article can be seen as a factor graph. VSLAM systems usually have a (kind of bipartite) factor graph with vertices/variables that are either keyframes or ‘good’ features, with edges/factors between features and the frames that see them and between adjacent frames; each of these edges are the factors in the graph. This structure results in very large but sparse graphs, and there are factor graph optimization libraries that take advantage of this sparsity (e.g. g2o or GTSAM.) These libraries also use specialized optimization techniques for some of the nonlinear manifolds (e.g. SO(3)) that arise in SLAM problems.

> impersonating Nat Friedman using a bug in GitHub's application.

This is not a bug, it's a part of how Git fundamentally works. If you want to mitigate it you have to sign your commits. GitHub could only attribute commits in the UI if they're signed, but I suspect that this is considered too much friction to enable.