As easy as downloading an app from the store and telling it which directory to work with.
If you need the AI features those require separate apps and depending on your deployment it might need some effort. I'm running a docker image and had to ensure I have some of the required libraries for the AI things to work. It isn't too hard to misconfigure though and I believe there's a decent amount of resources for this.
As for mobile app, there isn't an explicit one but the webapp interface is mobile friendly and works pretty well. I also use NC photos and it still works with the tags and face recognition things. That app doesn't require "Memories" as far as I know.
How complex is it to configure memories? I own a hosted instance of NextCloud from Hetzner, but I would rather not misconfigure it. Also, is there a mobile app? I think not having one is limiting, since most of the time I want to look at the pictures on the phone
There is a sequel on homological methods, which is not online, and I am currently trying to publish both. When I have time, I would like to write a third volume on homotopical methods (essentially all the stuff needed for André-Quillen cohomology and the cotangent complex).
> who needs interpretation when compile times are that fast!
Well, interpretation is pretty useful for a REPL. And a REPL is not just useful to avoid compilation, but also as a way to explore a new API. And, most importantly, to preserve the results of long computations when you do not know yet what to do with it. If computing a value takes half an hour, you certainly don't want to recompute it each time you change something. Rather, you keep an open session, such as a REPL or a notebook, and keep computing with the already existing value
This is one of the aspects that self professed R/Python datascience contenders often get wrong. The very bare minimum is a well supported and thought out dataframe library. Without that, the language is basically dead in the water. Nim seems to have a very well thought out API that also avoids many of the annoying aspects of Pandas (e.g. the huge waste coming from eagerly computing each vectorized operation into separate arrays).
Most of my work is time series analysis and I refuse to use an environment where samples are not explicitly labelled/timestamped and where the tooling does not support seamless operations that take this labeling into account.
So for my use case, a fully featured dataframe library is indeed a must.
See my comment from the other reply on this question for potential solutions, but as an fyi for those curious, Nim does come with a VIM that comes in very handy for such purposes: https://nim-lang.org/docs/nims.html
Had a project once where 70% or so of the 8 month runtime was de/serialization. 800gb or so data wad and 16gb of ram; all messily multiply interlinked and not even the indexes would fit into ram. it sucked.
but the architecture that imposed meat we were surprisingly resilient to power outages.
Am I the only one who likes what King Crimson did until the 70s, and does not understand the direction they went with Discipline? I have tried listening to it and later albums, but I never got it. Anyone here can help me better appreciate King Crimson's music from the 80s on?
There's plenty of music I "ought" to like based on my general music interest but don't really care all that much for, or even dislike. I don't really know what makes me really like or dislike a particular piece of music, but it's pretty common for things to just not resonate with me.
For what it's worth, I never really appreciated King Crimson beyond the 70s either. Don't ask me why; in any objective sense they're a fantastic band and I can definitely appreciate their music to that degree, but for one reason or the other it just doesn't truly resonate with me shrug
I don't think there's a frame of mind or rationalization that can make you appreciate an album more. Personally I think Discipline is alright but I prefer other albums, even THRAK which came later.
Is the option to buy prints still there? Some services offer the possibility to buy prints on canvas tied on a wooden frame, possibly manually retouched, which look much like an actual picture you can hang in your living room
