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

Put it in a pair of jeans and you have captured the very essence of Lemmy in a single image.

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.

Right, that’s it, we’re removing the network and power connections too.

To be fair, I’ve had my share of foul ups on remote servers too, but I have noone to complain to but myself about that.

01000001 00100000 01110011 01110100 01100101 01100001 01100100 01111001 00100000 01101000 01100001 01101110 01100100 00100000 01100001 01101110 01100100 00100000 01100001 00100000 01101101 01100001 01100111 01101110 01100101 01110100 01101001 01110011 01100101 01100100 00100000 01101110 01100101 01100101 01100100 01101100 01100101 00101110

I mean, if you’re not using LFS, are you really using linux at all?

To be fair, it would slightly reduce the xhance of the user really messing it up. If they remove the screen too we might finally have a user-proof computer. No more “I’ve forgotten my password”, no more “I put the internet in the trash can and now I can’t find it”, and no more “I didn’t do anything (they absolutely did) and now it doesn’t work, this must be your fault. (As the local ‘techie’ it’s not my fault, but it probably is my problem). Fix it!! (sigh…)”

There are certainly better ways, but I suspect this way is cheaper as the only need to stock one connector type.

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.

Edit the config was useful if you were trying to hook up a more unusual monitor that had odd timings or more overscan than a normal one, but it was definitely arcane magic.

Really Starting To Understand Very Xanthous Yammering Zarvanites.

They are, but by definition, the printer can print them. If your on linux or Mac it looks like it might be possible to write a filter to add to CUPS that would do it for every print.

Black and white printers can’t do that, but as I mentioned in another comnent, if you do have a color printer, add lots of yellow dots before you print it out.

If you’ve got a printer that does that, add lots of yellow dots to your document before printing it.

Great! Had I Just Known Little More, Now Only Peaceful Questions.

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.