It’s a bit of a stretch calling it a plastic, as it’s not petroleum based from what I’ve read.

It might, possibly, be a viable use case if the LLM produced the summary for an editor, who then confirmed it’s veracity and appropriateness to the article and posted it themselves.

Could you let me know what sort of models you’re using? Everything I’ve tried has basically been so bad it was quicker and more reliable to to the job myself. Most of the models can barely write boilerplate code accurately and securely, let alone anything even moderately complex.

I’ve tried to get them to analyse code too, and that’s hit and miss at best, even with small programs. I’d have no faith at all that they could handle anything larger; the answers they give would be confident and wrong, which is easy to spot with something small, but much harder to catch with a large, multi process system spread over a network. It’s hard enough for humans, who have actual context, understanding and domain knowledge, to do it well, and I’ve, personally, not seen any evidence that an LLM (which is what I’m assuming you’re referring to) could do anywhere near as well. I don’t doubt that they flag some issues, but without a comprehensive, human, review of the system architecture, implementation and code, you can’t be sure what they’ve missed, and if you’re going to do that anyway, you’ve done the job yourself!

Having said that, I’ve no doubt that things will improve, programming languages have well defined syntaxes and so they should be some of the easiest types of text for an LLM to parse and build a context from. If that can be combined with enough domain knowledge, a description of the deployment environment and a model that’s actually trained for and tuned for code analysis and security auditing, it might be possible to get similar results to humans.

I’m unlikely to do a full code audit, unless something about it doesn’t pass the ‘sniff test’. I will often go over the main code flows, the issue tracker, mailing lists and comments, positive or negative, from users on other forums.

I mean, if you’re not doing that, what are you doing, just installing it and using it??!? Where’s the fun in that? (I mean this at least semi seriously, you learn a lot about the software you’re running if you put in some effort to learn about it)

‘AI’ as we currently know it, is terrible at this sort of task. It’s not capable of understanding the flow of the code in any meaningful way, and tends to raise entirely spurious issues (see the problems the curl author has with being overwhealmed for example). It also wont spot actually malicious code that’s been included with any sort of care, nor would it find intentional behaviour that would be harmful or counterproductive in the particular scenario you want to use the program.

A valid point, trackers often give you a certain amount of upload credit for free, and there are often other ways to earn those credits too, so all users’ ratios would be above 1.0, but that should have read “A closed group of users can all have a seed ratio of 1.0” if we’re looking at just the data transfer itself.

A closed group of users can all have a seed ratio above 1.0, but it’s a bit of a contrived set up. For simplicity, in the following examples we assume that each file is the same size, but this also works for other combinations.

Consider the smallest group, two users. If user A seeds a file and user B downloads it, whilst B seeds a different file, which A downloads, both users will have a ratio of 1.0 as they’ve up and down loaded the same amount.

For three users, A seeds a file, B and C then download a different half each, which they then share with each other. A has a total (upload, download) of (1,0), whilst B and C have (0.5,1). If you repeat this with B seeding and A and C downloading, then C seeding to A and B, you get each peer uploading 2 files worth of data, and downloading 2 files worth, for a ratio of 1.0 each.

You can keep adding peers and keep the ratios balanced, so it is possible for all the users on a private tracker to have a 1.0 ratio, but it’s very unlikely to work out like that in real life, which is why you have other ways to boost your ratio.

If roll thrusters fired because the star tracker drifted and if the heater was still off, then an explosion would destroy Voyager 1.

That is some high stakes remote maintenance. I don’t want to imaging the stress for everybody involved. The relief when they finally got a signal two days later confirming the craft was still in obe piece and the heater was on must have been immense. I get stressed enough waiting minutes for a remote server to come back up.

DSN Canberra upgrade will cause loss of comms until Feb 2026

Oh great, another stressful wait!

You dismiss the data you recorded because it doesn’t seem to support your hypothysis tgat there is greater lag in wayland, but that’s not really the right approach, and I think it points to a different conclusion.

You recorded a lag of 5 or 6 frames at 90 frames per second in both Xorg and wayland, which suggests that the lag is the same to within 0.011 seconds, and I don’t think that you can say that’s a huge difference. However, what you didn’t test is the acceleration curve on mouse movement. If that curve is different under wayland it could easily feel infuriatingly laggy without actually showing any extra delay on the movement starting or ending.

I’m not sure how you’d accurately test that, a HID device just sending mouse move events wouldn’t do it as wouldn’t mimic you accelerating the mouse from stationary, so wouldn’t exercise the acceleration curve in wayland. You might need a physical device that moves your actual mouse a fixed dustance and then measure the distance the cursor moves on screen. Repeat for different movement speeds and you might have sone useful data.