Probably a similar step from practical effects to computer rendered effects. Gain some, loose some, and best results will probably be gotten with a mixed technique made by professionals who know what they are doing.

Don’t go crazy about abstraction.

Sometimes it’s better to write some code twice than expending two weeks trying to make a fit-all new class with 50 interfaces.

Sometimes you should do that, but for many projects that level of abstraction is not needed.

Astrology, but penguin themed.

You are such a Debian.

Arch and Gentoos never got along.

If you are a Nix do not install KDE on the first monday of the month, it’s bad luck.

I never trust that move. I’m fairly sure that they only do that so they can crawl themselves and sell the data.

I’ve always said. It’s not good that cloudfare (or any single entity) “owns” half the internet.

For my self hosted stuff I refuse to use their services. I prefer to invest a little more time securing it from my side instead of giving them more control over internet.

You have to get familiar with the codebase at some point. When you are unfamiliar, in my experience, LLMs can provide help understanding it. Copying large portions of code you don’t really understand and asking for an analysis and explanation.

Not so far ago I used it on assembly code. It would have taken ages to decipher what it was doing by myself. The AI sped up the process.

But once you are very familiar with a established project you had work a lot with, I don’t even bother asking LLMs anything, as in my experience, I come up with better answers quicker.

At the end of the day we must understand that a LLM is more or less an statistical autocomplete trained on a large dataset. If your solution is not on the dataset the thing is not going to really came up with a creative solution. And the thing is not going to run a debugger on your code either, afaik.

When I use it the question I ask myself the most before bothering is “is the solution likely to be on the training dataset?” or “is it a task that can be solved as a language problem?”

I find it more useful doing large language transformations and delving into unknown patterns, languages or environments.

If I know a source head to toe, and I’m proficient with that environment, it’s going to offer little help. Specially if it’s a highly specialized problem.

Since SVB crash there have been firings left and right. I suspect AI is only an excuse for them.

The study was centered on bugfixing large established projects. This task is not really the one that AI helpers excel at.

Also small number of participants (16) , the participants were familiar with the code base and all tasks seems to be smaller in completion time can screw results.

Thus the divergence between studio results and many people personal experience that would experience increase of productivity because they are doing different tasks in a different scenario.

Best ping is 127.0.0.1

It always resolves!

Chatgpt is just enforcing 4th law of robotics.

I have no mouth and I must scream.

It was originally published as part of a book compilation, and it was kind of hard to find a file with just that story and without typos all over the place.

4741

One small old book that used to be hard to find in good quality. I’ve it seeding for years, and being so small and in risk of being lost I’ve never taken it down.

Do you have a proper robots.txt file?

Do they do weird things like invalid url, invalid post tries? Weird user agents?

Millions of times by the same ip sound much more like vulnerability proving than crawler.

If that’s the case fail to ban or crowdsec. Should be easy to set up a rule to ban an inhumane number of hits per second on certain resources.

How do you know it’s “AI” scrappers?

I’ve have my server up before AI was a thing.

It’s totally normal to get thousands of bot hits and to get scraped.

I use crowdsec to mitigate it. But you will always get bot hits.

Histeria clickbait makes money. Extra points if some kind of agenda can be pushed so more people share.

Nah. That analogy does not work.

Piracy situation is more like you have made a cool statue and you charge people money for looking at your statue. Then someone comes, looks at your statue, and goes away without paying.

There’s no thief, nothing was stolen at any point. The one how came looking without paying was probably never going to pay for an entrance, and the statue can me still be looked by anyone. Nothing is loss in the process, no harm is done. Some guy just looked at a statue without paying for it.

Piglet is still there in the morning though.

I have it on docker with two volumes, ./config and ./cache

I back up those before each update.

A bad Jellyfin update should not mess with your media folder in anyway. Though you should have backups of those aswell as a rule of thumb.

A good human translator is always the best solution.

But if the choice would be between crappy google translate or a LLM I would take the LLM translation.

There’s no excuse for a big studio, they should hire translators. But for indie creators without a budget it can be the best way to get their creation to more people.

I’ve been using jellyfin for years.

My best recommendation is DELAY UPDATES and back up before you update.

I have a history of updates breaking everything so you should be careful about them.

All software recommends backing up before an update, but for jellyfin the shit is real, you really want to back up.