This year's advent of code is already over. I had started it with an energetic optimism that fueled my belief that "This year I'm gonna do it all! I am even gonna do it twice in a new language!". Obviously, like many others, I hope, I ended up solving something like the first 10 days in Python and the first 3 in Rust. I then dedicated myself solely to food coma, gaming and exploring old towns.

After a few years of using Emacs mainly for smaller side projects or scripting, I have started to integrate it more and more into my daily work, turning it slowly but surely into my main IDE. Although PyCharm still has a couple of tools which I can't resist abandoning (namely the Conflict Resolution action and the execution configurations), I am starting to feel that with Emacs 28 built with native compilation and native json support, I do not miss much from outside Emacs, and all the newer tools like counsel, vertico, project.

Since the advent of language server protocols (LSP) and the default inclusion of native JSON parsing in Emacs, I've read online several blog articles and watched videos from System Crafters on how things have improved for the text editor (although it can be used as a OS). Moreover, the experimental project mode gives a built-in project management that seems to have fewer features than projectile, but provides a ready-to-use tool which requires minimal configuration, if none at all, to be already useful.

The problem While building a webapp for text analysis and NLP things, I noticed that the project was getting bigger than expected, and having everything run in a single monolithic dash instance was too messy. Therefore, I started looking into how I could combine several dash instances, while still working on a single project and single api server. Needless to say, it was a bit tricky at times, and Dash requires you to do some silly things if you want to decouple and organize your project into several modules.

Unsupervised Vowels The difference between supervised and unsupervised learning is that the first requires human help to learn to categorize data, while the latter does not need anything more than the data itself to learn and propose its own classification groups. In the future A.I. will conquer the world with supercyborgs, at least that's what I got from tabloids, so it would be better for these cyborg to learn how to distinguish between a u and a i, otherwise there might be the chance that instead of "fire!

There are many ways to represent words, texts, or even speech. One thing they have in common is that, excluding idioms and aphorisms, it's impossible for two texts or speeches to be the same, because there is a lot of variation in the words and phrases they contain. An exception to this, however, are poems and songs. Poems and songs rely on repetition not only of melodies but also of words and phrases.