Badabinski

The segmented caching request thing is… weird. I worked for a company that developed a caching proxy and it very much did not work that way. Like, random access in a caching system is usually kinda bad and you should try to avoid it. Like, our proxy manually controlled the disk (it wasn’t a mounted filesystem) so it could constantly sweep the head across the disk and cue up reads and writes optimally. This gets much harder when things are fragmented as fuck.

If the concern was about what would happen with multiple connections for the same cache miss, then the caching proxy should just combine the client-side connections into a single upstream one. You can still cache the first part of the response if your upstream connection gets terminated and then restart it from that point.

ASA can still warp, but an enclosed and warm build chamber should do a lot to squelch that. Are you printing on an open bed slinger? Or do you already have a build chamber?

God, the fucking comment spam drives me absolutely fucking nuts. I used to enjoy reading 2 consecutive changes with 12 lines of comments because it meant I was in for a hell of a story of woe and misery. Now, it’s just the fucking slop machine doing its thing.

With regards to LLMs being good enough to do our jobs, I don’t think that’s ever going to happen. Token prediction is a neat trick, but you actually need something that can reason and understand to replace human intellect, and nothing I’ve seen on the horizon appears to be capable of that.

Yes, there’s far more code to review and the reviews are extremely fucking frustrating and I can tell who is using an LLM based on the volume and texture of the shit they’re pushing out. You have to check everything excreted by an LLM far more thoroughly than if it had just been written by the senior dev who produced the slop. An LLM is incapable of reasoning, it’s just choosing likely tokens based on past context, so nothing it produces can actually be trusted.

Source—I’m a senior dev at a large software company you’ve absolutely heard of. I am drowning in slop.

Yeah, it’s so fucking frustrating. I felt conflicted writing this because I don’t want to reduce anyone’s resistance to the garbage being pushed by the big corpos. We should be saying “no” as strongly as possible at every encroachment. I just also don’t want essential research to also take the blow. A lot of environmental research benefits from satellite imagery, and anything we can do to glean more information from that is a good thing.

Damned if you do, damned if you don’t. You can’t really expect the average person to learn the distinction between the good and the bad here. You can try to educate folks, but people already have enough shit on their plates as it is.

This is why “AI” is such a shit term. This is not a general purpose generative model, which is what you (and me) should (and very clearly do) dislike.

This is a model that is designed to operate on a very specific set of data and extract information from it. It was created by people at the University of Cambridge, not one of the big shitty companies. It’s not something that you run all the time, it’s something you only run when gathering data for research purposes. The model was trained on truly freely available data. No nonconsensual large-scale scraping was used to train this model, so it’s free of the ethical concerns typically associated with “AI”. Since it’s something a research group would run by themselves on a single (albeit very powerful) machine, it has very modest power requirements.

Models like this have been around for at least 15 years in the research space, and they don’t deserve your ire. It’s one of the truly good uses of ML.

If you want more details on the system, it’s all open source and can be found here: https://github.com/ucam-eo/tessera

EDIT: Please don’t take this as me trying to defend LLMs and image generators. I fucking hate LLMs and image generators. People at my workplace have described me as “the anti-AI guy” because I really am. I think almost all of the ML products made by OpenAI, Anthropic, and others are unethical and also just shit.

Where’s the CVE? Was there an attempt at responsible disclosure? Was confidentiality breached? Did they coordinate this release with the devs like the dirtyfrag people did? This “announcement” doesn’t answer any of these questions and I am frustrated by it.

EDIT: Ok, there IS a CVE: https://security-tracker.debian.org/tracker/CVE-2026-46300

There are far more bountiful resources to be found, including GitHub issues with concrete examples. I picked that one because I know that all four of the companies listed are problematic. I do not currently have the time to find more detailed links, but they’re out there.

Here’s just one sample that came up when I searched for “3d printer GPL violation”

https://www.th3dstudio.com/2018/04/05/gpl-violations-in-the-3d-printer-community-creality-anet-tronxy-zonestar-and-others/

If you get some PETG V0 or ABS V0, that will be perfectly safe and probably up to code. That shit can self extinguish when it catches on fire.

yeah, like, supposedly it can be hard to use GPL with some rust dependencies, but the MPL is right there as a decent compromise.