Order by string desc would be Z-A ordering, or 9-0

ORDER BY str(Hour) DESC: 9, 8, 7, 6, 5, 4, 3, 2, 12, 11, 10, 1

ORDER BY int(Hour) DESC: 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1

I think she forgot to breathe.

Oh. Thanks for sharing!

Thank you, this is exactly my thought. I really want to use GIMP, i just literally can’t. I even managed to get used to Inkscape as an ex Illustrator user. I would say I can use any random graphics designer tool after roughly 20 minutes of getting used to the UI, since most of the workflows are copied from others. GIMP always wanted to be different. And that’s the reason it never got popular and it will stay like that, unless something changes.

Maybe, someone will be able to use the GIMP core and put a revamped UI on top of it. Call it LIMP to minimize anger from GIMP evangelists.

Disagree. The product is awesome. The commercialization not. I beg to differ.

The UI of GIMP sucked and still sucks. Nothing is going to change that.

After using so many different tools, on all platforms, with great or shitty UI, I have seen it all — I still hate GIMP.

I am using SiYuan and I use the web app as a short cut, so that I can easily create notes on my phone.

And 46% have no idea what a database is.

I see what you are saying and this is true for the things that land on Trump’s table and include thr SCOTUS. All other things will be handled according to law and if not, a judge will help out.

Of course not. Now enjoy replying to anyone requesting it manually, as it is a government funded report and you have to release it on request.

Probably an effect of DOGE, by showing they were saving money on employees and server costs, without knowing the consequences of making it probably a magnitude more expensive than it was before DOGE came.

Wait. I know how to cure the MAGA’s.

And this is why I do not like K8s at all. The only reason to use it is to have something on your CV. Besides that, Docker Swarm and Hashicorp Nomad feel a lot better and are a lot easier to manage.

Good luck with cooling down unmoderated plutonium.

Dems: “You are sooooo mean!!” - Ha, that will show him for sure!

9 petabytes of raw data have been produced with the EHT in 2017 and 2018. After filtering, only about 100 terabytes were left. After final calibrations, about 150 gigabytes were then used to generate the images.

So clearly a lot of data was thrown away, as it was not usable for generating images. However, a machine learning model might be able to use this data.

Oh, they don’t train on image data. They train on raw sensor data. And as mentioned earlier, they used all the data that was too noisy to produce images out of it.

Fully agree, overfitting might be an issue. We don’t know how much training data was available. Just more than the first assumption suggests. But it might still not be enough.

To clarify: they used data which was determined as unusable as it was too noisy for regular algorithms. So the neural net was trained on more data than just a couple of images. They were trained on all the raw data available. Even if the results might not be that accurate, it is actually a good way of solving this type of problem. Scientifically speaking, the results are not accurate, but it might give us a new perspective to the problem.

My favorite book 🥹