In my part of the world both of these are true, and proudly so. We keep catching a myriad of errors, big and small. The history is easy to read, and helps anyone catching up with how a certain project evolved.

I understand it might not be true for everyone, every team, in every line of business; but this sort of discipline pays off in quality oboth of the code _and_ the team members' abilities.

Comments URL: https://news.ycombinator.com/item?id=43686016

Points: 29

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=40627515

Points: 16

# Comments: 0

Funny how different people's experiences can be. When Chrome came out in 2008 I remember trying it just for fun (more than once), and it never clicked with me, so I stayed with Firefox.

What was harder for me was keeping with all the unnecessary redesigns, empty eye candy, dumbing down, the Fennec debacle (exensions used to work, then they suddenly stopped for a bunch of years; plus, no keyword search for no reason).

By that time staying away from Google had become a goal in itself, but I understand who migrated to chrome.

Anyway, I am firmly convinced Chrome won because of Google's abuse of its web search monopoly. The innovations that its team introduced were groundbreaking from a technical point of view, but Firefox was a perfectly capable browser.

I both find it respectful of who wrote the answer in the first place and useful for future users of the code: the Stack Overflow answer often provides context and explanation for what would otherwise be an obscure piece of code.

Pretty darn useful if you ask me: those who want to have more information can follow the link, casual readers can skip it, and the whole process if fair to the author.

It does not break the web. It may break single sites that were written on naive assumptions; I see a lot of sites break because my extensions do not allow loading analytics libraries. This means their js was dependent on this libraries being actually active.

I'd say this is case a case of _unbreaking_ the web.

Different harmonics have different ADSR curves (Attack, Decay, Sustain, Release).

Above all, one cannot overstress the importance of the attack transient. There are famous experiments in psychoacoustics that show that, when deprived of their attack transient, the sounds of two different instruments may become hard to tell apart.

Personal anecdote: as a classic guitarist, it took me three years of experimentation to find the right way to cut my fingernails in order to have a better sound. The Electronic Engineer in me says that those were three years spent to look for how to improve 0.1 seconds of noise at the start of each of my notes.

Music is a language, even if with no semantic. It has conventions, dialects, a syntax, a grammar. There are multiple dimensions a musician uses to convey what he wants/feels: just like an actor has to control at the same time its voice, posture, interplay with other actors, so a good musician is aware of the structure of the piece he is composing/executing, the relations between the various subparts, how the musical discourse progresses in time, besides agogic, dynamics, sound color.

All of those aspects are continually perpetually compared against the conventions of the genre, mixed, evolved, strictly followed or balatantly negated.

This is something that normally a professional musician takes decades to master (apart from musical geniuses).

A listener takes less time to educate himself to appreciate those nuances (but not too little: let's say ~years). Once you develop a taste, it becomes very obvious to see through the spectrum that goes from bad quality tunes to musical artistry.

I see nothing musically interesting in this (wonderful) PoC of speech synthesis.

Just to be clear: I did not see anything particularly stunning even in Google's Bach Doodle from some years ago https://doodles.google/doodle/celebrating-johann-sebastian-b...

Musically, however, I can't help but notice that these models are still very far from being able to generate something interesting: from harmony, to tempo, to musical structure, to dynamics, everything is muddled and without structure. I guess there is still very much to work on, and I am not sure that purely generative models can attain higher levels. Maybe a mixed rule-based and generative approach would do?

The progress is really fast in this field, I really do not know.

    import subprocess
    [...]
    result = subprocess.run(["wakeonlan", "MY:MA:CA:DD:RE:SS"], capture_output=True)

For example, one could take inspiration from the code at https://github.com/remcohaszing/pywakeonlan/blob/main/wakeon...

Is there an officially supported CLI for Signal? Please tell me it's true, that would mean so much for small scale automation!