Damn what the hell. I’m Dutch and I pay less than €12 euros. For that I get 100 call minutes/messages and 6 GB. Neither of which I ever really get close to. Calling is mostly just in case of emergency or when we need to align something right now. And data is always useful because I definitely do not have free wifi anywhere. Do you never leave a big city or something? If I slip with my bike on an icy road and break something in the middle of nowhere it’s kinda good to have some way of communicating.

You call it “quick to judge and superficial”, but imo that’s the wrong attitude. Every tool we use as humans should be designed to be as intuitive as possible. It makes it easiest for people to learn how to use a new tool. That doesn’t mean that a tool cannot be complex or customizable, but the default experience should make it easy for new users to quickly achieve something. Once they grow accustomed to the tool they can tailor it their own way.

No tool has to do this, but if it wants to be widely used then this is kinda necessary.

There’s a reason why there are whole fields of study into human media interaction, and why software companies hire UI designers. Everything that doesn’t have to be explained in words and text because it is intuitive saves mental overhead for the user and makes the application more accessible.

Can, but not by default. The default setup is what leaves an impression on most users. Most users opening GIMP for the first time expect to be able to find stuff that they need, not have to first spend a lot of time getting familiar with all of its options. It shouldn’t be needed to first spend time opening all the sane default windows and re-aliging stuff every time you boot it for the first time. At least, that shouldn’t be the case of GIMP wants to be as popular with non-technical users like Krita is.

Also, the tool bar still doesn’t have the nice separations between tool functions, and it still feel a bit more chaotic. Not sure of it’s the icons or the order.

Now admittedly I’m not someone who often uses drawing programs, but my biggest issue in GIMP is that I never seem to be able to find what I’m looking for.

In the two images you posted you can actually see an example of such a case. In Krita all the tools (or whatever you’d call them) in the bar on the left are ordered in a logical way, and separate types of tools are also visually separated by separator lines. The bar with tools is also only 2 icons wide, which makes scanning for the right tool a bit easier, since you can mostly just scan along the vertical axis. In GIMP it’s just a pile of low contrast icons in seemingly random order. Unless you’ve used it enough to know the order, you’re gonna have to do a lot more searching. And searching will be way harder since you’ll have to search horizontally and vertically.

It’s like reading a website where the text is taking the whole with of the screen and without paragraphs (GIMP) vs reading a website where the line length is constrained, the text is horizontally centered, and there are proper paragraphs.

I feel like this example reflects my personal experience with both. I’ve used quite a few different types of image editing programs, and with most of them I can fairly easily find the stuff I need. Using GIMP however, I used to be quite lost. Nowadays it’s gotten better because the windows are not all floating around and I’ve used it more. But still, I only found Krita after using a fair bit of GIMP, and yet I felt instantly more at home because the UI was easier to navigate.

Edit: That being said, GIMP is a very cool program. I don’t want to hate on it too much. It’s helped me countless times. The UI has already improved a lot since the floaty window days, and I hope that continues.

KeePass2Android also has those luckily

Obviously this is a privacy community, and this ain’t great in that regard, but as someone who’s interested in AI this is absolutely fascinating. I’m now starting to wonder whether the model could theoretically encode the entire dataset in its weights. Surely some compression and generalization is taking place, otherwise it couldn’t generate all the amazing responses it does give to novel inputs, but apparently it can also just recite long chunks of the dataset. And also why would these specific inputs trigger such a response. Maybe there are issues in the training data (or process) that cause it to do this. Or maybe this is just a fundamental flaw of the model architecture? And maybe it’s even an expected thing. After all, we as humans also have the ability to recite pieces of “training data” if we seem them interesting enough.